lexpit-class {blm} | R Documentation |

## Class "lexpit"

### Description

Class for linear-expit regression (lexpit).

### Objects from the Class

Objects can be created by calls of the form `new("lexpit", ...)`

.

### Slots

`coef.linear`

:vector of fitted linear coefficients

`coef.expit`

:vector of fitted expit coefficients

`vcov.linear`

:matrix of variance-covariate estimates for linear

`coef`

`vcov.expit`

:matrix of variance-covariate estimates for expit

`coef`

`formula.linear`

:model formula for linear component

`formula.expit`

:model formula for expit component

`df.residual`

:residual degrees of freedom

`p`

:number of linear parameters

`q`

:number of expit parameters

`data`

:data frame used in fitting, after applying

`na.action`

`which.kept`

:vector of index of values in original data source that were used in the model fitting

`y`

:response vector for fitted model

`weights`

:vector of weights used in model fitting

`strata`

:stratification factor for weighted regression.

`converged`

:logical message about convergence status at the end of algorithm

`par.init`

:initial parameter values for optimization algorithm

`loglik`

value of log-likelihood (normalized for weighted likelihood) under full model

`loglik.null`

value of log-likelihood (normalized for weighted likelihood) under null model

`barrier.value`

value of the barrier function at the optimum

`control.lexpit`

list with control parameters for optimization algorithm

### Methods

- show
`signature(object = "lexpit")`

: Display point estimates of`lexpit`

object.`signature(x = "lexpit",...)`

: Display point estimates of`lexpit`

object.- summary
`signature(object = "lexpit",...)`

: List of estimates and convergence information.- coef
`signature(object = "lexpit")`

: Extractor for fitted coefficients.- logLik
`signature(object = "lexpit")`

: Extractor for log-likelihood of`lexpit`

model.- model.formula
`signature(object = "lexpit")`

: Extractor for formula of`lexpit`

object.- vcov
`signature(object = "lexpit")`

: Extractor for variance-covariance based on Taylor series large-sample Hessian approximation with the pseudo-likelihood of the constrained optimization.- resid
`signature(object = "lexpit")`

: Extractor for residuals.- predict
`signature(object = "lexpit")`

: Returns vector of linear predictors for each subject of the fitted model.- confint
`signature(object = "lexpit", parm, level = 0.95,...)`

: Returns confidence interval (at a given`level`

) for the specified regression parameters.

### See Also

*blm*version 2022.0.0.1 Index]