02-yai.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "02 - `yai`\n==========\n\n- ***`yai`*** finds kNNs given reference and, optionally, target observations. \n- This function is the main function in the package. \n- It returns an object of class `yai`. \n- A key role played in this function is to separate the observations into reference and target observations. \n\n### Target and Reference Values\n\n- Target observations are those with values for X variables and not for Y variables\n- Reference observations are those with no missing values for X and Y variables.\n"
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "install.packages(c(\"yaImpute\",\"ccaPP\"))\nlibrary(yaImpute)\nlibrary(ccaPP)                 ",
      "execution_count": 11,
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": "Installing packages into '/home/nbcommon/R'\n(as 'lib' is unspecified)\n"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "data(iris)\n# set the random number seed so that example results are consistent\n# normally, leave out this command\nset.seed(12345)\n# form some test data, y's are defined only for reference\n# observations.\nrefs=sample(rownames(iris),50)\nhead(refs,6)\nx <- iris[,1:2] # Sepal.Length Sepal.Width\nhead(x,3)\ny <- iris[refs,3:4] # Petal.Length Petal.Width\nhead(y,3)",
      "execution_count": 14,
      "outputs": [
        {
          "data": {
            "text/html": "<ol class=list-inline>\n\t<li>'109'</li>\n\t<li>'131'</li>\n\t<li>'113'</li>\n\t<li>'149'</li>\n\t<li>'67'</li>\n\t<li>'25'</li>\n</ol>\n",
            "text/latex": "\\begin{enumerate*}\n\\item '109'\n\\item '131'\n\\item '113'\n\\item '149'\n\\item '67'\n\\item '25'\n\\end{enumerate*}\n",
            "text/markdown": "1. '109'\n2. '131'\n3. '113'\n4. '149'\n5. '67'\n6. '25'\n\n\n",
            "text/plain": "[1] \"109\" \"131\" \"113\" \"149\" \"67\"  \"25\" "
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": "<table>\n<thead><tr><th scope=col>Sepal.Length</th><th scope=col>Sepal.Width</th></tr></thead>\n<tbody>\n\t<tr><td>5.1</td><td>3.5</td></tr>\n\t<tr><td>4.9</td><td>3.0</td></tr>\n\t<tr><td>4.7</td><td>3.2</td></tr>\n</tbody>\n</table>\n",
            "text/latex": "\\begin{tabular}{r|ll}\n Sepal.Length & Sepal.Width\\\\\n\\hline\n\t 5.1 & 3.5\\\\\n\t 4.9 & 3.0\\\\\n\t 4.7 & 3.2\\\\\n\\end{tabular}\n",
            "text/markdown": "\nSepal.Length | Sepal.Width | \n|---|---|---|\n| 5.1 | 3.5 | \n| 4.9 | 3.0 | \n| 4.7 | 3.2 | \n\n\n",
            "text/plain": "  Sepal.Length Sepal.Width\n1 5.1          3.5        \n2 4.9          3.0        \n3 4.7          3.2        "
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/html": "<table>\n<thead><tr><th></th><th scope=col>Petal.Length</th><th scope=col>Petal.Width</th></tr></thead>\n<tbody>\n\t<tr><th scope=row>109</th><td>5.8</td><td>1.8</td></tr>\n\t<tr><th scope=row>131</th><td>6.1</td><td>1.9</td></tr>\n\t<tr><th scope=row>113</th><td>5.5</td><td>2.1</td></tr>\n</tbody>\n</table>\n",
            "text/latex": "\\begin{tabular}{r|ll}\n  & Petal.Length & Petal.Width\\\\\n\\hline\n\t109 & 5.8 & 1.8\\\\\n\t131 & 6.1 & 1.9\\\\\n\t113 & 5.5 & 2.1\\\\\n\\end{tabular}\n",
            "text/markdown": "\n| <!--/--> | Petal.Length | Petal.Width | \n|---|---|---|\n| 109 | 5.8 | 1.8 | \n| 131 | 6.1 | 1.9 | \n| 113 | 5.5 | 2.1 | \n\n\n",
            "text/plain": "    Petal.Length Petal.Width\n109 5.8          1.8        \n131 6.1          1.9        \n113 5.5          2.1        "
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": false
      },
      "cell_type": "code",
      "source": "# build yai objects using 2 methods\nmsn <- yai(x=x,y=y)\nmal <- yai(x=x,y=y,method=\"mahalanobis\")",
      "execution_count": 15,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "# compare these results using the generalized mean distances. mal wins!\ngrmsd(mal,msn)\n",
      "execution_count": 16,
      "outputs": [
        {
          "data": {
            "text/html": "<dl class=dl-horizontal>\n\t<dt>mal</dt>\n\t\t<dd>1.00728457207218</dd>\n\t<dt>msn</dt>\n\t\t<dd>1.24643717375406</dd>\n</dl>\n",
            "text/latex": "\\begin{description*}\n\\item[mal] 1.00728457207218\n\\item[msn] 1.24643717375406\n\\end{description*}\n",
            "text/markdown": "mal\n:   1.00728457207218msn\n:   1.24643717375406\n\n",
            "text/plain": "     mal      msn \n1.007285 1.246437 "
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### ccaPP\nCanonical Correlation Analysis via Projection Pursuit"
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "# use projection pursuit and specify \"ppControl\". \n# This reqires package ccaPP.\nmsnPP <- yai(x=x,y=y,method=\"msnPP\",ppControl=c(method=\"kendall\",search=\"proj\"))\n\ngrmsd(mal,msnPP,msn)\n",
      "execution_count": 18,
      "outputs": [
        {
          "data": {
            "text/html": "<dl class=dl-horizontal>\n\t<dt>mal</dt>\n\t\t<dd>1.00728457207218</dd>\n\t<dt>msnPP</dt>\n\t\t<dd>1.07498327092616</dd>\n\t<dt>msn</dt>\n\t\t<dd>1.24643717375406</dd>\n</dl>\n",
            "text/latex": "\\begin{description*}\n\\item[mal] 1.00728457207218\n\\item[msnPP] 1.07498327092616\n\\item[msn] 1.24643717375406\n\\end{description*}\n",
            "text/markdown": "mal\n:   1.00728457207218msnPP\n:   1.07498327092616msn\n:   1.24643717375406\n\n",
            "text/plain": "     mal    msnPP      msn \n1.007285 1.074983 1.246437 "
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "data(MoscowMtStJoe)\n# convert polar slope and aspect measurements to cartesian\n# (which is the same as Stage's (1976) transformation).\npolar <- MoscowMtStJoe[,40:41]\npolar[,1] <- polar[,1]*.01 # slope proportion\npolar[,2] <- polar[,2]*(pi/180) # aspect radians",
      "execution_count": 19,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": false
      },
      "cell_type": "code",
      "source": "cartesian <- t(apply(polar,1,function (x)\n{return (c(x[1]*cos(x[2]),x[1]*sin(x[2]))) }))\n\ncolnames(cartesian) <- c(\"xSlAsp\",\"ySlAsp\")",
      "execution_count": 20,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "x <- cbind(MoscowMtStJoe[,37:39],cartesian,MoscowMtStJoe[,42:64])\nhead(x,3)",
      "execution_count": 21,
      "outputs": [
        {
          "data": {
            "text/html": "<table>\n<thead><tr><th scope=col>EASTING</th><th scope=col>NORTHING</th><th scope=col>ELEVMEAN</th><th scope=col>xSlAsp</th><th scope=col>ySlAsp</th><th scope=col>B1MEAN</th><th scope=col>B2MEAN</th><th scope=col>B3MEAN</th><th scope=col>B4MEAN</th><th scope=col>B5MEAN</th><th scope=col>...</th><th scope=col>INTMIN</th><th scope=col>INTMAX</th><th scope=col>HTMEAN</th><th scope=col>HTSTD</th><th scope=col>HTMIN</th><th scope=col>HTMAX</th><th scope=col>CCMEAN</th><th scope=col>CCSTD</th><th scope=col>CCMIN</th><th scope=col>CCMAX</th></tr></thead>\n<tbody>\n\t<tr><td>571920.0   </td><td>5234917    </td><td> 774.2451  </td><td>-0.2660646 </td><td>-0.10091865</td><td>1357.875   </td><td>1146.750   </td><td>826.125    </td><td>537.25     </td><td>1210.750   </td><td>...        </td><td>54         </td><td>151        </td><td>32.364     </td><td>2.460      </td><td>28         </td><td>37         </td><td>90.682     </td><td>10.835     </td><td>67         </td><td>100        </td></tr>\n\t<tr><td>568367.9   </td><td>5224512    </td><td>1036.8050  </td><td> 0.1530449 </td><td>-0.08691548</td><td>1234.750   </td><td> 990.250   </td><td>591.250    </td><td>305.75     </td><td> 924.500   </td><td>...        </td><td>38         </td><td>160        </td><td>29.727     </td><td>3.466      </td><td>21         </td><td>35         </td><td>97.864     </td><td> 4.994     </td><td>80         </td><td>100        </td></tr>\n\t<tr><td>571994.6   </td><td>5221844    </td><td>1714.9190  </td><td> 0.1013015 </td><td>-0.14528742</td><td>1116.143   </td><td> 880.857   </td><td>521.429    </td><td>261.00     </td><td> 541.714   </td><td>...        </td><td>50         </td><td>155        </td><td>27.524     </td><td>4.521      </td><td>18         </td><td>35         </td><td>88.952     </td><td> 6.644     </td><td>78         </td><td>100        </td></tr>\n</tbody>\n</table>\n",
            "text/latex": "\\begin{tabular}{r|llllllllllllllllllllllllllll}\n EASTING & NORTHING & ELEVMEAN & xSlAsp & ySlAsp & B1MEAN & B2MEAN & B3MEAN & B4MEAN & B5MEAN & ... & INTMIN & INTMAX & HTMEAN & HTSTD & HTMIN & HTMAX & CCMEAN & CCSTD & CCMIN & CCMAX\\\\\n\\hline\n\t 571920.0    & 5234917     &  774.2451   & -0.2660646  & -0.10091865 & 1357.875    & 1146.750    & 826.125     & 537.25      & 1210.750    & ...         & 54          & 151         & 32.364      & 2.460       & 28          & 37          & 90.682      & 10.835      & 67          & 100        \\\\\n\t 568367.9    & 5224512     & 1036.8050   &  0.1530449  & -0.08691548 & 1234.750    &  990.250    & 591.250     & 305.75      &  924.500    & ...         & 38          & 160         & 29.727      & 3.466       & 21          & 35          & 97.864      &  4.994      & 80          & 100        \\\\\n\t 571994.6    & 5221844     & 1714.9190   &  0.1013015  & -0.14528742 & 1116.143    &  880.857    & 521.429     & 261.00      &  541.714    & ...         & 50          & 155         & 27.524      & 4.521       & 18          & 35          & 88.952      &  6.644      & 78          & 100        \\\\\n\\end{tabular}\n",
            "text/markdown": "\nEASTING | NORTHING | ELEVMEAN | xSlAsp | ySlAsp | B1MEAN | B2MEAN | B3MEAN | B4MEAN | B5MEAN | ... | INTMIN | INTMAX | HTMEAN | HTSTD | HTMIN | HTMAX | CCMEAN | CCSTD | CCMIN | CCMAX | \n|---|---|---|\n| 571920.0    | 5234917     |  774.2451   | -0.2660646  | -0.10091865 | 1357.875    | 1146.750    | 826.125     | 537.25      | 1210.750    | ...         | 54          | 151         | 32.364      | 2.460       | 28          | 37          | 90.682      | 10.835      | 67          | 100         | \n| 568367.9    | 5224512     | 1036.8050   |  0.1530449  | -0.08691548 | 1234.750    |  990.250    | 591.250     | 305.75      |  924.500    | ...         | 38          | 160         | 29.727      | 3.466       | 21          | 35          | 97.864      |  4.994      | 80          | 100         | \n| 571994.6    | 5221844     | 1714.9190   |  0.1013015  | -0.14528742 | 1116.143    |  880.857    | 521.429     | 261.00      |  541.714    | ...         | 50          | 155         | 27.524      | 4.521       | 18          | 35          | 88.952      |  6.644      | 78          | 100         | \n\n\n",
            "text/plain": "  EASTING  NORTHING ELEVMEAN  xSlAsp     ySlAsp      B1MEAN   B2MEAN   B3MEAN \n1 571920.0 5234917   774.2451 -0.2660646 -0.10091865 1357.875 1146.750 826.125\n2 568367.9 5224512  1036.8050  0.1530449 -0.08691548 1234.750  990.250 591.250\n3 571994.6 5221844  1714.9190  0.1013015 -0.14528742 1116.143  880.857 521.429\n  B4MEAN B5MEAN   ... INTMIN INTMAX HTMEAN HTSTD HTMIN HTMAX CCMEAN CCSTD \n1 537.25 1210.750 ... 54     151    32.364 2.460 28    37    90.682 10.835\n2 305.75  924.500 ... 38     160    29.727 3.466 21    35    97.864  4.994\n3 261.00  541.714 ... 50     155    27.524 4.521 18    35    88.952  6.644\n  CCMIN CCMAX\n1 67    100  \n2 80    100  \n3 78    100  "
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "y <- MoscowMtStJoe[,1:35]\nhead(y,3)",
      "execution_count": 26,
      "outputs": [
        {
          "data": {
            "text/html": "<table>\n<thead><tr><th scope=col>ABGR_BA</th><th scope=col>ABLA_BA</th><th scope=col>ACGL_BA</th><th scope=col>BEOC_BA</th><th scope=col>LAOC_BA</th><th scope=col>PICO_BA</th><th scope=col>PIEN_BA</th><th scope=col>PIMO_BA</th><th scope=col>PIPO_BA</th><th scope=col>POBA_BA</th><th scope=col>...</th><th scope=col>PIMO_TD</th><th scope=col>PIPO_TD</th><th scope=col>POBA_TD</th><th scope=col>POTR_TD</th><th scope=col>PSME_TD</th><th scope=col>SAEX_TD</th><th scope=col>THPL_TD</th><th scope=col>TSHE_TD</th><th scope=col>TSME_TD</th><th scope=col>UNKN_TD</th></tr></thead>\n<tbody>\n\t<tr><td> 0.00000 </td><td>0.0000000</td><td>0        </td><td>0        </td><td> 0.00000 </td><td>0        </td><td>0.0000000</td><td>0        </td><td>0        </td><td>0        </td><td>...      </td><td>0        </td><td>0        </td><td>0        </td><td>0        </td><td>518.92084</td><td>0        </td><td>  0.0000 </td><td> 0.00000 </td><td>  0.0000 </td><td>12.35526 </td></tr>\n\t<tr><td>20.90473 </td><td>0.0000000</td><td>0        </td><td>0        </td><td>19.88266 </td><td>0        </td><td>0.5528975</td><td>0        </td><td>0        </td><td>0        </td><td>...      </td><td>0        </td><td>0        </td><td>0        </td><td>0        </td><td> 24.71052</td><td>0        </td><td>457.1446 </td><td>12.35526 </td><td>  0.0000 </td><td>12.35526 </td></tr>\n\t<tr><td> 0.00000 </td><td>0.7423694</td><td>0        </td><td>0        </td><td> 5.04691 </td><td>0        </td><td>0.9313407</td><td>0        </td><td>0        </td><td>0        </td><td>...      </td><td>0        </td><td>0        </td><td>0        </td><td>0        </td><td>  0.00000</td><td>0        </td><td>  0.0000 </td><td> 0.00000 </td><td>469.4998 </td><td> 0.00000 </td></tr>\n</tbody>\n</table>\n",
            "text/latex": "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllll}\n ABGR\\_BA & ABLA\\_BA & ACGL\\_BA & BEOC\\_BA & LAOC\\_BA & PICO\\_BA & PIEN\\_BA & PIMO\\_BA & PIPO\\_BA & POBA\\_BA & ... & PIMO\\_TD & PIPO\\_TD & POBA\\_TD & POTR\\_TD & PSME\\_TD & SAEX\\_TD & THPL\\_TD & TSHE\\_TD & TSME\\_TD & UNKN\\_TD\\\\\n\\hline\n\t  0.00000  & 0.0000000 & 0         & 0         &  0.00000  & 0         & 0.0000000 & 0         & 0         & 0         & ...       & 0         & 0         & 0         & 0         & 518.92084 & 0         &   0.0000  &  0.00000  &   0.0000  & 12.35526 \\\\\n\t 20.90473  & 0.0000000 & 0         & 0         & 19.88266  & 0         & 0.5528975 & 0         & 0         & 0         & ...       & 0         & 0         & 0         & 0         &  24.71052 & 0         & 457.1446  & 12.35526  &   0.0000  & 12.35526 \\\\\n\t  0.00000  & 0.7423694 & 0         & 0         &  5.04691  & 0         & 0.9313407 & 0         & 0         & 0         & ...       & 0         & 0         & 0         & 0         &   0.00000 & 0         &   0.0000  &  0.00000  & 469.4998  &  0.00000 \\\\\n\\end{tabular}\n",
            "text/markdown": "\nABGR_BA | ABLA_BA | ACGL_BA | BEOC_BA | LAOC_BA | PICO_BA | PIEN_BA | PIMO_BA | PIPO_BA | POBA_BA | ... | PIMO_TD | PIPO_TD | POBA_TD | POTR_TD | PSME_TD | SAEX_TD | THPL_TD | TSHE_TD | TSME_TD | UNKN_TD | \n|---|---|---|\n|  0.00000  | 0.0000000 | 0         | 0         |  0.00000  | 0         | 0.0000000 | 0         | 0         | 0         | ...       | 0         | 0         | 0         | 0         | 518.92084 | 0         |   0.0000  |  0.00000  |   0.0000  | 12.35526  | \n| 20.90473  | 0.0000000 | 0         | 0         | 19.88266  | 0         | 0.5528975 | 0         | 0         | 0         | ...       | 0         | 0         | 0         | 0         |  24.71052 | 0         | 457.1446  | 12.35526  |   0.0000  | 12.35526  | \n|  0.00000  | 0.7423694 | 0         | 0         |  5.04691  | 0         | 0.9313407 | 0         | 0         | 0         | ...       | 0         | 0         | 0         | 0         |   0.00000 | 0         |   0.0000  |  0.00000  | 469.4998  |  0.00000  | \n\n\n",
            "text/plain": "  ABGR_BA  ABLA_BA   ACGL_BA BEOC_BA LAOC_BA  PICO_BA PIEN_BA   PIMO_BA PIPO_BA\n1  0.00000 0.0000000 0       0        0.00000 0       0.0000000 0       0      \n2 20.90473 0.0000000 0       0       19.88266 0       0.5528975 0       0      \n3  0.00000 0.7423694 0       0        5.04691 0       0.9313407 0       0      \n  POBA_BA ... PIMO_TD PIPO_TD POBA_TD POTR_TD PSME_TD   SAEX_TD THPL_TD \n1 0       ... 0       0       0       0       518.92084 0         0.0000\n2 0       ... 0       0       0       0        24.71052 0       457.1446\n3 0       ... 0       0       0       0         0.00000 0         0.0000\n  TSHE_TD  TSME_TD  UNKN_TD \n1  0.00000   0.0000 12.35526\n2 12.35526   0.0000 12.35526\n3  0.00000 469.4998  0.00000"
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "msn <- yai(x=x, y=y, method=\"msn\", k=1)\n# msn",
      "execution_count": 27,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "mal <- yai(x=x, y=y, method=\"mahalanobis\", k=1)\n# mal",
      "execution_count": 28,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "# compare these results using the generalized mean distances..\ngrmsd(mal,msn)",
      "execution_count": 29,
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": "Warning message in grmsd(mal, msn):\n\"rank deficiency in mal was addressed by removing: SAEX_BA.o, POBA_TD.o, POTR_TD.o, SAEX_TD.o, SAEX_BA, POBA_TD, POTR_TD, SAEX_TD\"Warning message in grmsd(mal, msn):\n\"rank deficiency in msn was addressed by removing: SAEX_BA.o, POBA_TD.o, POTR_TD.o, SAEX_TD.o, SAEX_BA, POBA_TD, POTR_TD, SAEX_TD\""
        },
        {
          "data": {
            "text/html": "<dl class=dl-horizontal>\n\t<dt>msn</dt>\n\t\t<dd>1.25291072064258</dd>\n\t<dt>mal</dt>\n\t\t<dd>1.35761453790584</dd>\n</dl>\n",
            "text/latex": "\\begin{description*}\n\\item[msn] 1.25291072064258\n\\item[mal] 1.35761453790584\n\\end{description*}\n",
            "text/markdown": "msn\n:   1.25291072064258mal\n:   1.35761453790584\n\n",
            "text/plain": "     msn      mal \n1.252911 1.357615 "
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "# the results can be plotted.\nplot(mal,vars=yvars(mal)[1:16])\n\n\n",
      "execution_count": 30,
      "outputs": [
        {
          "data": {
            "image/png": 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wV0j+ra/7B5e3sfPHiQfXrkyBFvb2+ePE9cXDw7OzslJcXBwWHx4sUFBQVdLLDn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\nhmEYhmGYksANOwzDMAzDMCXxf2WKUOJNcIkKAAAAAElFTkSuQmCC",
            "text/plain": "plot without title"
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "# reduce the plant community data for randomForest.\nyba <- MoscowMtStJoe[,1:17]\nybaB <- whatsMax(yba,nbig=7) # see help on whatsMax\nrf <- yai(x=x, y=ybaB, method=\"randomForest\", k=1)\n# build the imputations for the original y's\nrforig <- impute(rf,ancillaryData=y)\n# compare the results using individual rmsd's\ncompare.yai(mal,msn,rforig)",
      "execution_count": 32,
      "outputs": [
        {
          "data": {
            "text/html": "<table>\n<thead><tr><th></th><th scope=col>mal.rmsdS</th><th scope=col>msn.rmsdS</th><th scope=col>rforig.rmsdS</th></tr></thead>\n<tbody>\n\t<tr><th scope=row>ABGR_BA</th><td>1.3320746</td><td>1.2299857</td><td>0.9143698</td></tr>\n\t<tr><th scope=row>ABLA_BA</th><td>1.4307948</td><td>0.9343005</td><td>1.2281613</td></tr>\n\t<tr><th scope=row>ACGL_BA</th><td>1.4124081</td><td>1.7288044</td><td>1.7308742</td></tr>\n\t<tr><th scope=row>BEOC_BA</th><td>1.1365392</td><td>1.0782388</td><td>2.0072885</td></tr>\n\t<tr><th scope=row>LAOC_BA</th><td>1.1544195</td><td>1.0281362</td><td>1.0701537</td></tr>\n\t<tr><th scope=row>PICO_BA</th><td>1.9825784</td><td>1.1165344</td><td>1.2763674</td></tr>\n\t<tr><th scope=row>PIEN_BA</th><td>1.3210013</td><td>1.1220116</td><td>1.2601067</td></tr>\n\t<tr><th scope=row>PIMO_BA</th><td>1.0481852</td><td>1.3349768</td><td>1.1312086</td></tr>\n\t<tr><th scope=row>PIPO_BA</th><td>1.5474435</td><td>1.8634704</td><td>0.8347220</td></tr>\n\t<tr><th scope=row>POBA_BA</th><td>1.0000000</td><td>1.0000000</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>POTR_BA</th><td>1.4142136</td><td>1.0000000</td><td>2.0000000</td></tr>\n\t<tr><th scope=row>PSME_BA</th><td>1.3501980</td><td>1.3211264</td><td>0.9918342</td></tr>\n\t<tr><th scope=row>SAEX_BA</th><td>1.0000000</td><td>1.0000000</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>THPL_BA</th><td>1.0392611</td><td>0.9180436</td><td>0.8274826</td></tr>\n\t<tr><th scope=row>TSHE_BA</th><td>1.4916014</td><td>1.1089766</td><td>1.2006016</td></tr>\n\t<tr><th scope=row>TSME_BA</th><td>1.5098452</td><td>1.0434446</td><td>0.7837448</td></tr>\n\t<tr><th scope=row>UNKN_BA</th><td>1.1160745</td><td>1.2160385</td><td>1.0551722</td></tr>\n\t<tr><th scope=row>Total_BA</th><td>0.9661392</td><td>0.6247194</td><td>0.6713762</td></tr>\n\t<tr><th scope=row>ABGR_TD</th><td>1.3780861</td><td>1.2567078</td><td>0.9676102</td></tr>\n\t<tr><th scope=row>ABLA_TD</th><td>1.2484815</td><td>1.0067283</td><td>1.2251234</td></tr>\n\t<tr><th scope=row>ACGL_TD</th><td>1.4098222</td><td>1.7244402</td><td>1.7289019</td></tr>\n\t<tr><th scope=row>BEOC_TD</th><td>1.0214843</td><td>1.0325277</td><td>2.0732773</td></tr>\n\t<tr><th scope=row>LAOC_TD</th><td>1.1529742</td><td>0.9343585</td><td>1.0107298</td></tr>\n\t<tr><th scope=row>PICO_TD</th><td>1.9314311</td><td>1.2284800</td><td>1.2460116</td></tr>\n\t<tr><th scope=row>PIEN_TD</th><td>1.1813655</td><td>1.0826578</td><td>1.2570742</td></tr>\n\t<tr><th scope=row>PIMO_TD</th><td>0.9411573</td><td>1.1262861</td><td>1.1140833</td></tr>\n\t<tr><th scope=row>PIPO_TD</th><td>1.5232918</td><td>1.6434870</td><td>1.0837312</td></tr>\n\t<tr><th scope=row>POBA_TD</th><td>1.0000000</td><td>1.0000000</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>POTR_TD</th><td>1.4142136</td><td>1.0000000</td><td>2.0000000</td></tr>\n\t<tr><th scope=row>PSME_TD</th><td>1.3549453</td><td>1.3436224</td><td>1.1443644</td></tr>\n\t<tr><th scope=row>SAEX_TD</th><td>1.0000000</td><td>1.0000000</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>THPL_TD</th><td>1.0629391</td><td>1.0259286</td><td>1.1418828</td></tr>\n\t<tr><th scope=row>TSHE_TD</th><td>1.5448054</td><td>1.0789090</td><td>1.1738829</td></tr>\n\t<tr><th scope=row>TSME_TD</th><td>1.5444733</td><td>1.0334274</td><td>0.7995150</td></tr>\n\t<tr><th scope=row>UNKN_TD</th><td>1.1237127</td><td>1.2290762</td><td>1.1475879</td></tr>\n</tbody>\n</table>\n",
            "text/latex": "\\begin{tabular}{r|lll}\n  & mal.rmsdS & msn.rmsdS & rforig.rmsdS\\\\\n\\hline\n\tABGR\\_BA & 1.3320746 & 1.2299857 & 0.9143698\\\\\n\tABLA\\_BA & 1.4307948 & 0.9343005 & 1.2281613\\\\\n\tACGL\\_BA & 1.4124081 & 1.7288044 & 1.7308742\\\\\n\tBEOC\\_BA & 1.1365392 & 1.0782388 & 2.0072885\\\\\n\tLAOC\\_BA & 1.1544195 & 1.0281362 & 1.0701537\\\\\n\tPICO\\_BA & 1.9825784 & 1.1165344 & 1.2763674\\\\\n\tPIEN\\_BA & 1.3210013 & 1.1220116 & 1.2601067\\\\\n\tPIMO\\_BA & 1.0481852 & 1.3349768 & 1.1312086\\\\\n\tPIPO\\_BA & 1.5474435 & 1.8634704 & 0.8347220\\\\\n\tPOBA\\_BA & 1.0000000 & 1.0000000 & 1.4142136\\\\\n\tPOTR\\_BA & 1.4142136 & 1.0000000 & 2.0000000\\\\\n\tPSME\\_BA & 1.3501980 & 1.3211264 & 0.9918342\\\\\n\tSAEX\\_BA & 1.0000000 & 1.0000000 & 1.4142136\\\\\n\tTHPL\\_BA & 1.0392611 & 0.9180436 & 0.8274826\\\\\n\tTSHE\\_BA & 1.4916014 & 1.1089766 & 1.2006016\\\\\n\tTSME\\_BA & 1.5098452 & 1.0434446 & 0.7837448\\\\\n\tUNKN\\_BA & 1.1160745 & 1.2160385 & 1.0551722\\\\\n\tTotal\\_BA & 0.9661392 & 0.6247194 & 0.6713762\\\\\n\tABGR\\_TD & 1.3780861 & 1.2567078 & 0.9676102\\\\\n\tABLA\\_TD & 1.2484815 & 1.0067283 & 1.2251234\\\\\n\tACGL\\_TD & 1.4098222 & 1.7244402 & 1.7289019\\\\\n\tBEOC\\_TD & 1.0214843 & 1.0325277 & 2.0732773\\\\\n\tLAOC\\_TD & 1.1529742 & 0.9343585 & 1.0107298\\\\\n\tPICO\\_TD & 1.9314311 & 1.2284800 & 1.2460116\\\\\n\tPIEN\\_TD & 1.1813655 & 1.0826578 & 1.2570742\\\\\n\tPIMO\\_TD & 0.9411573 & 1.1262861 & 1.1140833\\\\\n\tPIPO\\_TD & 1.5232918 & 1.6434870 & 1.0837312\\\\\n\tPOBA\\_TD & 1.0000000 & 1.0000000 & 1.4142136\\\\\n\tPOTR\\_TD & 1.4142136 & 1.0000000 & 2.0000000\\\\\n\tPSME\\_TD & 1.3549453 & 1.3436224 & 1.1443644\\\\\n\tSAEX\\_TD & 1.0000000 & 1.0000000 & 1.4142136\\\\\n\tTHPL\\_TD & 1.0629391 & 1.0259286 & 1.1418828\\\\\n\tTSHE\\_TD & 1.5448054 & 1.0789090 & 1.1738829\\\\\n\tTSME\\_TD & 1.5444733 & 1.0334274 & 0.7995150\\\\\n\tUNKN\\_TD & 1.1237127 & 1.2290762 & 1.1475879\\\\\n\\end{tabular}\n",
            "text/markdown": "\n| <!--/--> | mal.rmsdS | msn.rmsdS | rforig.rmsdS | \n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| ABGR_BA | 1.3320746 | 1.2299857 | 0.9143698 | \n| ABLA_BA | 1.4307948 | 0.9343005 | 1.2281613 | \n| ACGL_BA | 1.4124081 | 1.7288044 | 1.7308742 | \n| BEOC_BA | 1.1365392 | 1.0782388 | 2.0072885 | \n| LAOC_BA | 1.1544195 | 1.0281362 | 1.0701537 | \n| PICO_BA | 1.9825784 | 1.1165344 | 1.2763674 | \n| PIEN_BA | 1.3210013 | 1.1220116 | 1.2601067 | \n| PIMO_BA | 1.0481852 | 1.3349768 | 1.1312086 | \n| PIPO_BA | 1.5474435 | 1.8634704 | 0.8347220 | \n| POBA_BA | 1.0000000 | 1.0000000 | 1.4142136 | \n| POTR_BA | 1.4142136 | 1.0000000 | 2.0000000 | \n| PSME_BA | 1.3501980 | 1.3211264 | 0.9918342 | \n| SAEX_BA | 1.0000000 | 1.0000000 | 1.4142136 | \n| THPL_BA | 1.0392611 | 0.9180436 | 0.8274826 | \n| TSHE_BA | 1.4916014 | 1.1089766 | 1.2006016 | \n| TSME_BA | 1.5098452 | 1.0434446 | 0.7837448 | \n| UNKN_BA | 1.1160745 | 1.2160385 | 1.0551722 | \n| Total_BA | 0.9661392 | 0.6247194 | 0.6713762 | \n| ABGR_TD | 1.3780861 | 1.2567078 | 0.9676102 | \n| ABLA_TD | 1.2484815 | 1.0067283 | 1.2251234 | \n| ACGL_TD | 1.4098222 | 1.7244402 | 1.7289019 | \n| BEOC_TD | 1.0214843 | 1.0325277 | 2.0732773 | \n| LAOC_TD | 1.1529742 | 0.9343585 | 1.0107298 | \n| PICO_TD | 1.9314311 | 1.2284800 | 1.2460116 | \n| PIEN_TD | 1.1813655 | 1.0826578 | 1.2570742 | \n| PIMO_TD | 0.9411573 | 1.1262861 | 1.1140833 | \n| PIPO_TD | 1.5232918 | 1.6434870 | 1.0837312 | \n| POBA_TD | 1.0000000 | 1.0000000 | 1.4142136 | \n| POTR_TD | 1.4142136 | 1.0000000 | 2.0000000 | \n| PSME_TD | 1.3549453 | 1.3436224 | 1.1443644 | \n| SAEX_TD | 1.0000000 | 1.0000000 | 1.4142136 | \n| THPL_TD | 1.0629391 | 1.0259286 | 1.1418828 | \n| TSHE_TD | 1.5448054 | 1.0789090 | 1.1738829 | \n| TSME_TD | 1.5444733 | 1.0334274 | 0.7995150 | \n| UNKN_TD | 1.1237127 | 1.2290762 | 1.1475879 | \n\n\n",
            "text/plain": "         mal.rmsdS msn.rmsdS rforig.rmsdS\nABGR_BA  1.3320746 1.2299857 0.9143698   \nABLA_BA  1.4307948 0.9343005 1.2281613   \nACGL_BA  1.4124081 1.7288044 1.7308742   \nBEOC_BA  1.1365392 1.0782388 2.0072885   \nLAOC_BA  1.1544195 1.0281362 1.0701537   \nPICO_BA  1.9825784 1.1165344 1.2763674   \nPIEN_BA  1.3210013 1.1220116 1.2601067   \nPIMO_BA  1.0481852 1.3349768 1.1312086   \nPIPO_BA  1.5474435 1.8634704 0.8347220   \nPOBA_BA  1.0000000 1.0000000 1.4142136   \nPOTR_BA  1.4142136 1.0000000 2.0000000   \nPSME_BA  1.3501980 1.3211264 0.9918342   \nSAEX_BA  1.0000000 1.0000000 1.4142136   \nTHPL_BA  1.0392611 0.9180436 0.8274826   \nTSHE_BA  1.4916014 1.1089766 1.2006016   \nTSME_BA  1.5098452 1.0434446 0.7837448   \nUNKN_BA  1.1160745 1.2160385 1.0551722   \nTotal_BA 0.9661392 0.6247194 0.6713762   \nABGR_TD  1.3780861 1.2567078 0.9676102   \nABLA_TD  1.2484815 1.0067283 1.2251234   \nACGL_TD  1.4098222 1.7244402 1.7289019   \nBEOC_TD  1.0214843 1.0325277 2.0732773   \nLAOC_TD  1.1529742 0.9343585 1.0107298   \nPICO_TD  1.9314311 1.2284800 1.2460116   \nPIEN_TD  1.1813655 1.0826578 1.2570742   \nPIMO_TD  0.9411573 1.1262861 1.1140833   \nPIPO_TD  1.5232918 1.6434870 1.0837312   \nPOBA_TD  1.0000000 1.0000000 1.4142136   \nPOTR_TD  1.4142136 1.0000000 2.0000000   \nPSME_TD  1.3549453 1.3436224 1.1443644   \nSAEX_TD  1.0000000 1.0000000 1.4142136   \nTHPL_TD  1.0629391 1.0259286 1.1418828   \nTSHE_TD  1.5448054 1.0789090 1.1738829   \nTSME_TD  1.5444733 1.0334274 0.7995150   \nUNKN_TD  1.1237127 1.2290762 1.1475879   "
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "cell_type": "code",
      "source": "\n\nplot(compare.yai(mal,msn,rforig))\n# build another randomForest case forcing regression\n# to be used for continuous variables. The answers differ\n# but one is not clearly better than the other.\nrf2 <- yai(x=x, y=ybaB, method=\"randomForest\", rfMode=\"regression\")\nrforig2 <- impute(rf2,ancillaryData=y)\ncompare.yai(rforig2,rforig)\n",
      "execution_count": 33,
      "outputs": [
        {
          "data": {
            "text/html": "<table>\n<thead><tr><th></th><th scope=col>rforig2.rmsdS</th><th scope=col>rforig.rmsdS</th></tr></thead>\n<tbody>\n\t<tr><th scope=row>ABGR_BA</th><td>1.1118244</td><td>0.9143698</td></tr>\n\t<tr><th scope=row>ABLA_BA</th><td>1.3167797</td><td>1.2281613</td></tr>\n\t<tr><th scope=row>ACGL_BA</th><td>2.0010285</td><td>1.7308742</td></tr>\n\t<tr><th scope=row>BEOC_BA</th><td>1.5400293</td><td>2.0072885</td></tr>\n\t<tr><th scope=row>LAOC_BA</th><td>0.9997220</td><td>1.0701537</td></tr>\n\t<tr><th scope=row>PICO_BA</th><td>1.0787768</td><td>1.2763674</td></tr>\n\t<tr><th scope=row>PIEN_BA</th><td>1.4119463</td><td>1.2601067</td></tr>\n\t<tr><th scope=row>PIMO_BA</th><td>1.1323121</td><td>1.1312086</td></tr>\n\t<tr><th scope=row>PIPO_BA</th><td>1.2378290</td><td>0.8347220</td></tr>\n\t<tr><th scope=row>POBA_BA</th><td>1.4142136</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>POTR_BA</th><td>1.4142136</td><td>2.0000000</td></tr>\n\t<tr><th scope=row>PSME_BA</th><td>0.9990758</td><td>0.9918342</td></tr>\n\t<tr><th scope=row>SAEX_BA</th><td>1.4142136</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>THPL_BA</th><td>1.0670007</td><td>0.8274826</td></tr>\n\t<tr><th scope=row>TSHE_BA</th><td>0.8607480</td><td>1.2006016</td></tr>\n\t<tr><th scope=row>TSME_BA</th><td>1.2378639</td><td>0.7837448</td></tr>\n\t<tr><th scope=row>UNKN_BA</th><td>1.4121713</td><td>1.0551722</td></tr>\n\t<tr><th scope=row>Total_BA</th><td>0.9197885</td><td>0.6713762</td></tr>\n\t<tr><th scope=row>ABGR_TD</th><td>1.0370109</td><td>0.9676102</td></tr>\n\t<tr><th scope=row>ABLA_TD</th><td>1.4015978</td><td>1.2251234</td></tr>\n\t<tr><th scope=row>ACGL_TD</th><td>2.0015026</td><td>1.7289019</td></tr>\n\t<tr><th scope=row>BEOC_TD</th><td>1.5724108</td><td>2.0732773</td></tr>\n\t<tr><th scope=row>LAOC_TD</th><td>0.8820691</td><td>1.0107298</td></tr>\n\t<tr><th scope=row>PICO_TD</th><td>1.0281799</td><td>1.2460116</td></tr>\n\t<tr><th scope=row>PIEN_TD</th><td>1.5081493</td><td>1.2570742</td></tr>\n\t<tr><th scope=row>PIMO_TD</th><td>1.1165345</td><td>1.1140833</td></tr>\n\t<tr><th scope=row>PIPO_TD</th><td>1.2580595</td><td>1.0837312</td></tr>\n\t<tr><th scope=row>POBA_TD</th><td>1.4142136</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>POTR_TD</th><td>1.4142136</td><td>2.0000000</td></tr>\n\t<tr><th scope=row>PSME_TD</th><td>1.0733156</td><td>1.1443644</td></tr>\n\t<tr><th scope=row>SAEX_TD</th><td>1.4142136</td><td>1.4142136</td></tr>\n\t<tr><th scope=row>THPL_TD</th><td>0.8946047</td><td>1.1418828</td></tr>\n\t<tr><th scope=row>TSHE_TD</th><td>0.9186476</td><td>1.1738829</td></tr>\n\t<tr><th scope=row>TSME_TD</th><td>1.2558952</td><td>0.7995150</td></tr>\n\t<tr><th scope=row>UNKN_TD</th><td>1.4489258</td><td>1.1475879</td></tr>\n</tbody>\n</table>\n",
            "text/latex": "\\begin{tabular}{r|ll}\n  & rforig2.rmsdS & rforig.rmsdS\\\\\n\\hline\n\tABGR\\_BA & 1.1118244 & 0.9143698\\\\\n\tABLA\\_BA & 1.3167797 & 1.2281613\\\\\n\tACGL\\_BA & 2.0010285 & 1.7308742\\\\\n\tBEOC\\_BA & 1.5400293 & 2.0072885\\\\\n\tLAOC\\_BA & 0.9997220 & 1.0701537\\\\\n\tPICO\\_BA & 1.0787768 & 1.2763674\\\\\n\tPIEN\\_BA & 1.4119463 & 1.2601067\\\\\n\tPIMO\\_BA & 1.1323121 & 1.1312086\\\\\n\tPIPO\\_BA & 1.2378290 & 0.8347220\\\\\n\tPOBA\\_BA & 1.4142136 & 1.4142136\\\\\n\tPOTR\\_BA & 1.4142136 & 2.0000000\\\\\n\tPSME\\_BA & 0.9990758 & 0.9918342\\\\\n\tSAEX\\_BA & 1.4142136 & 1.4142136\\\\\n\tTHPL\\_BA & 1.0670007 & 0.8274826\\\\\n\tTSHE\\_BA & 0.8607480 & 1.2006016\\\\\n\tTSME\\_BA & 1.2378639 & 0.7837448\\\\\n\tUNKN\\_BA & 1.4121713 & 1.0551722\\\\\n\tTotal\\_BA & 0.9197885 & 0.6713762\\\\\n\tABGR\\_TD & 1.0370109 & 0.9676102\\\\\n\tABLA\\_TD & 1.4015978 & 1.2251234\\\\\n\tACGL\\_TD & 2.0015026 & 1.7289019\\\\\n\tBEOC\\_TD & 1.5724108 & 2.0732773\\\\\n\tLAOC\\_TD & 0.8820691 & 1.0107298\\\\\n\tPICO\\_TD & 1.0281799 & 1.2460116\\\\\n\tPIEN\\_TD & 1.5081493 & 1.2570742\\\\\n\tPIMO\\_TD & 1.1165345 & 1.1140833\\\\\n\tPIPO\\_TD & 1.2580595 & 1.0837312\\\\\n\tPOBA\\_TD & 1.4142136 & 1.4142136\\\\\n\tPOTR\\_TD & 1.4142136 & 2.0000000\\\\\n\tPSME\\_TD & 1.0733156 & 1.1443644\\\\\n\tSAEX\\_TD & 1.4142136 & 1.4142136\\\\\n\tTHPL\\_TD & 0.8946047 & 1.1418828\\\\\n\tTSHE\\_TD & 0.9186476 & 1.1738829\\\\\n\tTSME\\_TD & 1.2558952 & 0.7995150\\\\\n\tUNKN\\_TD & 1.4489258 & 1.1475879\\\\\n\\end{tabular}\n",
            "text/markdown": "\n| <!--/--> | rforig2.rmsdS | rforig.rmsdS | \n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| ABGR_BA | 1.1118244 | 0.9143698 | \n| ABLA_BA | 1.3167797 | 1.2281613 | \n| ACGL_BA | 2.0010285 | 1.7308742 | \n| BEOC_BA | 1.5400293 | 2.0072885 | \n| LAOC_BA | 0.9997220 | 1.0701537 | \n| PICO_BA | 1.0787768 | 1.2763674 | \n| PIEN_BA | 1.4119463 | 1.2601067 | \n| PIMO_BA | 1.1323121 | 1.1312086 | \n| PIPO_BA | 1.2378290 | 0.8347220 | \n| POBA_BA | 1.4142136 | 1.4142136 | \n| POTR_BA | 1.4142136 | 2.0000000 | \n| PSME_BA | 0.9990758 | 0.9918342 | \n| SAEX_BA | 1.4142136 | 1.4142136 | \n| THPL_BA | 1.0670007 | 0.8274826 | \n| TSHE_BA | 0.8607480 | 1.2006016 | \n| TSME_BA | 1.2378639 | 0.7837448 | \n| UNKN_BA | 1.4121713 | 1.0551722 | \n| Total_BA | 0.9197885 | 0.6713762 | \n| ABGR_TD | 1.0370109 | 0.9676102 | \n| ABLA_TD | 1.4015978 | 1.2251234 | \n| ACGL_TD | 2.0015026 | 1.7289019 | \n| BEOC_TD | 1.5724108 | 2.0732773 | \n| LAOC_TD | 0.8820691 | 1.0107298 | \n| PICO_TD | 1.0281799 | 1.2460116 | \n| PIEN_TD | 1.5081493 | 1.2570742 | \n| PIMO_TD | 1.1165345 | 1.1140833 | \n| PIPO_TD | 1.2580595 | 1.0837312 | \n| POBA_TD | 1.4142136 | 1.4142136 | \n| POTR_TD | 1.4142136 | 2.0000000 | \n| PSME_TD | 1.0733156 | 1.1443644 | \n| SAEX_TD | 1.4142136 | 1.4142136 | \n| THPL_TD | 0.8946047 | 1.1418828 | \n| TSHE_TD | 0.9186476 | 1.1738829 | \n| TSME_TD | 1.2558952 | 0.7995150 | \n| UNKN_TD | 1.4489258 | 1.1475879 | \n\n\n",
            "text/plain": "         rforig2.rmsdS rforig.rmsdS\nABGR_BA  1.1118244     0.9143698   \nABLA_BA  1.3167797     1.2281613   \nACGL_BA  2.0010285     1.7308742   \nBEOC_BA  1.5400293     2.0072885   \nLAOC_BA  0.9997220     1.0701537   \nPICO_BA  1.0787768     1.2763674   \nPIEN_BA  1.4119463     1.2601067   \nPIMO_BA  1.1323121     1.1312086   \nPIPO_BA  1.2378290     0.8347220   \nPOBA_BA  1.4142136     1.4142136   \nPOTR_BA  1.4142136     2.0000000   \nPSME_BA  0.9990758     0.9918342   \nSAEX_BA  1.4142136     1.4142136   \nTHPL_BA  1.0670007     0.8274826   \nTSHE_BA  0.8607480     1.2006016   \nTSME_BA  1.2378639     0.7837448   \nUNKN_BA  1.4121713     1.0551722   \nTotal_BA 0.9197885     0.6713762   \nABGR_TD  1.0370109     0.9676102   \nABLA_TD  1.4015978     1.2251234   \nACGL_TD  2.0015026     1.7289019   \nBEOC_TD  1.5724108     2.0732773   \nLAOC_TD  0.8820691     1.0107298   \nPICO_TD  1.0281799     1.2460116   \nPIEN_TD  1.5081493     1.2570742   \nPIMO_TD  1.1165345     1.1140833   \nPIPO_TD  1.2580595     1.0837312   \nPOBA_TD  1.4142136     1.4142136   \nPOTR_TD  1.4142136     2.0000000   \nPSME_TD  1.0733156     1.1443644   \nSAEX_TD  1.4142136     1.4142136   \nTHPL_TD  0.8946047     1.1418828   \nTSHE_TD  0.9186476     1.1738829   \nTSME_TD  1.2558952     0.7995150   \nUNKN_TD  1.4489258     1.1475879   "
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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m7fvr2srIwQUl5efunSJWVlZTU1NT5uBWj35s2biRMnOjo6pqenv379WkdHZ+zY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DA9kZ8hDsasjCwmLFihWEEHrworS0lMvl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            "text/plain": "plot without title"
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": false
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": false
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": false
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": true,
        "trusted": false
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "r",
      "display_name": "R",
      "language": "R"
    },
    "language_info": {
      "mimetype": "text/x-r-source",
      "name": "R",
      "pygments_lexer": "r",
      "version": "3.4.1",
      "file_extension": ".r",
      "codemirror_mode": "r"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}