resistance

Artificial dataset. The experiment consists in measure the resistance to death of two types of tumor-cells over different doses of a experimental drug. The data was created considering a null intercept and a cubic polinomial for the dose.

datasets

It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.

Christian Galarza

Robust Linear Quantile Regression

resistance function

This data frame contains the following columns:<dl>
 <dt>dose</dt>
<dd>Quantity of dose of an experimental drug.</dd> <dt>type</dt>
<dd>Type of tumor-cell. Type A and B.</dd> <dt>score</dt>
<dd>Bounded response between 0 and 4.</dd> 
</dl>

Format

Tumor-cell resistance to death — resistance

This data frame contains the following columns:<dl>
 <dt>dose</dt>
<dd>Quantity of dose of an experimental drug.</dd>

 <dt>type</dt>
<dd>Type of tumor-cell. Type A and B.</dd>

 <dt>score</dt>
<dd>Bounded response between 0 and 4.</dd>

 
</dl>

resistance: Tumor-cell resistance to death

Description

Arguments

Format

Details