NpdeData-class: Class "NpdeData" representing the structure of the...

In npde: Normalised prediction distribution errors for nonlinear mixed-effect models

Description

A longitudinal data structure

Objects from the Class

NpdeData objects are typically created by calls to npdeData and contain the following slots:

name.data

character string giving the name of the dataset

name.group

character string giving the name of the grouping term (ID)

name.predictor

character string giving the name of the predictor (X)

name.response

character string giving the name of the response (Y)

name.cens

character string giving the name of the censoring indicator

name.mdv

character string giving the name of the missing data indicator

name.covariates

vector of character string giving the name(s) of the covariates

name.ipred

character string giving the name of the individual predictions

units

(optional) a list with the units for X, Y, and covariates

data

a dataframe containing the data

N

number of subjects

ntot.obs

total number of non-missing observations

nind.obs

vector of size N giving the number of non-missing observations for each subject

ind

index of non-missing observations

icens

index of censored observations (non-missing)

not.miss

a vector of boolean indicating for each observation whether it is missing (FALSE) or available (TRUE)

loq

the censoring value

Methods

npdeData(name.data):

Create a new NpdeData object from dataset name.data

print(npde.data):

Prints a summary of object npde.data

show(npde.data):

Prints a short summary of object npde.data

showall(npde.data):

Prints a detailed summary of object npde.data

plot(npde.data):

Plots the data in npde.data. More details can be found in plot.NpdeData

summary(npde.data):

Returns a summary of object npde.data in list format

set.npde.plotoptions(npde.data):

Sets options for graphs of npde.data (internal method used in plots)

See Also

npde, autonpde, plot.NpdeData

Examples

methods(class="NpdeData")

showClass("NpdeData")

npde documentation built on May 2, 2019, 5:23 p.m.