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          <h2>Advanced Regression Models</h2>
<p>Each of the regression analysis below contains working code examples with brief use-case explanations covered for each of the regression types in the list below. Many of these code snippets are generic enough so you could use them as a base template to start and build up on for your analyses.</p>
<p>Please note that the information presented in these pages should not be construed as full and complete analysis, but rather as a template and a hand guide of available modeling options. You are advised to pursue independent and thorough research before arriving at conclusions.</p>
<table>
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<col width="46%" />
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<thead>
<tr class="header">
<th align="left">METHOD</th>
<th align="left">APPLICATION CASE</th>
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<tr class="odd">
<td align="left"><a href="Robust-Regression-With-R.html">Robust Regression</a></td>
<td align="left">Applicable in all cases where OLS regression can be used. Applies re-weighting to reduce outlier influence.</td>
</tr>
<tr class="even">
<td align="left"><a href="Logistic-Regression-With-R.html">Logistic Regression</a></td>
<td align="left">Models binary variables.</td>
</tr>
<tr class="odd">
<td align="left"><a href="Probit-Regression-With-R.html">Probit Regression</a></td>
<td align="left">Models binary variables.</td>
</tr>
<tr class="even">
<td align="left"><a href="Multinomial-Regression-With-R.html">Multinomial Regression</a></td>
<td align="left">Models categorical variables with more that 2 levels.</td>
</tr>
<tr class="odd">
<td align="left"><a href="Ordinal-Logistic-Regression-With-R.html">Ordinal Logistic</a></td>
<td align="left">Models ordinal or rank variables.</td>
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<td align="left"><a href="Poisson-and-Negative-Binomial-Regression-With-R.html">Poisson and Negative Binomial</a></td>
<td align="left">Models count variables. Neg Binomial is used when there is over-dispersion.</td>
</tr>
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<td align="left"><a href="Ridge-Regression-With-R.html">Ridge Regression</a></td>
<td align="left">Address Multicollinearity</td>
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<td align="left"><a href="Beta-Regression-With-R.html">Beta Regression</a></td>
<td align="left">Models variables within (0, 1) range.</td>
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<td align="left"><a href="Dirichlet-Regression-With-R.html">Dirichlet Regression</a></td>
<td align="left">Models compositional data</td>
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<td align="left"><a href="Loess-Regression-With-R.html">Loess Regression</a></td>
<td align="left">Smoothing Time series.</td>
</tr>
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<td align="left"><a href="Isotonic-Regression-With-R.html">Isotonic Regression</a></td>
<td align="left">For approximation of data that can only increase (..typically cumulative data)</td>
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</table>


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