glmEstimation

An object of type <code><a rd-options="tm" href="/link/DocumentTermMatrix?package=SentimentAnalysis&version=1.3-4&to=tm" data-mini-rdoc="tm::DocumentTermMatrix">DocumentTermMatrix</a></code>.

Response variable including the given gold standard.

response

(optional) A list of parameters defining the model as follows:<ul>
<li>"family"Distribution for response variable. Default is <code>family="gaussian"</code>.
For non-negative counts, use <code>family="poisson"</code>. For binary variables
<code>family="binomial"</code>. See <code><a rd-options="" href="/link/glm?package=SentimentAnalysis&version=1.3-4" data-mini-rdoc="SentimentAnalysis::glm">glm</a></code> for further details.</li>
</ul>

control

Additional parameters passed to function for <code><a rd-options="" href="/link/glm?package=SentimentAnalysis&version=1.3-4" data-mini-rdoc="SentimentAnalysis::glm">glm</a></code>.

Function estimates coefficients based on generalized least squares.

Performs a sentiment analysis of textual contents in R. This implementation
utilizes various existing dictionaries, such as Harvard IV, or finance-specific
dictionaries. Furthermore, it can also create customized dictionaries. The latter
uses LASSO regularization as a statistical approach to select relevant terms based on
an exogenous response variable.

Nicolas Proellochs

SentimentAnalysis

Dictionary-Based Sentiment Analysis

Stefan Feuerriegel

glmEstimation function

<dl><dt>x</dt>
<dd>An object of type <code><a href="/link/DocumentTermMatrix?package=SentimentAnalysis&version=1.3-4" data-mini-rdoc="SentimentAnalysis::DocumentTermMatrix">DocumentTermMatrix</a></code>.</dd>
<dt>response</dt>
<dd>Response variable including the given gold standard.</dd>
<dt>control</dt>
<dd>(optional) A list of parameters defining the model as follows:<ul>
<li>"family"Distribution for response variable. Default is <code>family="gaussian"</code>.
For non-negative counts, use <code>family="poisson"</code>. For binary variables
<code>family="binomial"</code>. See <code><a href="/link/glm?package=SentimentAnalysis&version=1.3-4" data-mini-rdoc="SentimentAnalysis::glm">glm</a></code> for further details.</li>
</ul></dd>
<dt>...</dt>
<dd>Additional parameters passed to function for <code><a href="/link/glm?package=SentimentAnalysis&version=1.3-4" data-mini-rdoc="SentimentAnalysis::glm">glm</a></code>.</dd></dl>

Arguments

Estimation via generalized least squares — glmEstimation

<dl>

<dt>x</dt>
<dd>An object of type <code><a href='https://rdrr.io/pkg/tm/man/matrix.html'>DocumentTermMatrix</a></code>.</dd>


<dt>response</dt>
<dd>Response variable including the given gold standard.</dd>


<dt>control</dt>
<dd>(optional) A list of parameters defining the model as follows:<ul>
<li>"family"Distribution for response variable. Default is <code>family="gaussian"</code>.
For non-negative counts, use <code>family="poisson"</code>. For binary variables
<code>family="binomial"</code>. See <code><a href='https://rdrr.io/r/stats/glm.html'>glm</a></code> for further details.</li>
</ul></dd>


<dt>...</dt>
<dd>Additional parameters passed to function for <code><a href='https://rdrr.io/r/stats/glm.html'>glm</a></code>.</dd>

</dl>

glmEstimation: Estimation via generalized least squares

Description

Usage

Value

Arguments