| Package | Description |
|---|---|
| dev.nm.stat.regression.linear |
Linear regression problems, fitted coefficients, and diagnostics.
|
| dev.nm.stat.regression.linear.glm | |
| dev.nm.stat.regression.linear.glm.quasi | |
| dev.nm.stat.regression.linear.lasso | |
| dev.nm.stat.regression.linear.logistic | |
| dev.nm.stat.regression.linear.ols | |
| dev.nm.stat.regression.linear.residualanalysis | |
| dev.nm.stat.test.regression.linear.heteroskedasticity |
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMDiagnostics
This class collects some diagnostics measures for the goodness of fit based on the residulas for
a linear regression model.
|
| LMInformationCriteria
The information criteria measure the goodness of fit of an estimated statistical model.
|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
| Class and Description |
|---|
| LMResiduals
This is the residual analysis of the results of a linear regression model.
|
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