seqQuickLook: Summary of the types of gaps among a dataset

In seqimpute: Imputation of Missing Data in Sequence Analysis

Summary of the types of gaps among a dataset

Description

The seqQuickLook() function aimed at providing an overview of the number and size of the different types of gaps spread in the original dataset.

Usage

seqQuickLook(data, var = NULL, np = 1, nf = 1)

Arguments

data	a data.frame where missing data are coded as NA or a state sequence object built with seqdef function
var	the list of columns containing the trajectories. Default is NULL, i.e. all the columns.
np	number of previous observations in the imputation model of the internal gaps.
nf	number of future observations in the imputation model of the internal gaps.

Details

The distinction between internal and SLG gaps depends on the number of previous (np) and future (nf) observations that are set for the MICT and MICT-timing algorithms.

Value

Returns a data.frame object that summarizes, for each type of gaps (Internal Gaps, Initial Gaps, Terminal Gaps, LEFT-hand side SLG, RIGHT-hand side SLG, Both-hand side SLG), the minimum length, the maximum length, the total number of gaps and the total number of missing they contain.

Author(s)

Andre Berchtold and Kevin Emery

Examples

data(gameadd)

seqQuickLook(data = gameadd, var = 1:4, np = 1, nf = 1)

seqimpute documentation built on May 29, 2024, 4:35 a.m.