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latrend (version 1.1.2)

interface-featureBased: featureBased interface

Description

featureBased interface

Usage

# S4 method for lcMethodFeature
getName(object)
# S4 method for lcMethodFeature
getShortName(object)
# S4 method for lcMethodFeature
prepareData(method, data, verbose, ...)
# S4 method for lcMethodFeature
fit(method, data, envir, verbose, ...)
# S4 method for lcMethodGCKM
getName(object)
# S4 method for lcMethodGCKM
getShortName(object)
# S4 method for lcMethodGCKM
compose(method, envir = NULL)
# S4 method for lcMethodGCKM
preFit(method, data, envir, verbose)
# S4 method for lcMethodGCKM
fit(method, data, envir, verbose, ...)
# S4 method for lcMethodLMKM
getName(object)
# S4 method for lcMethodLMKM
getShortName(object)
# S4 method for lcMethodLMKM
prepareData(method, data, verbose)
# S4 method for lcMethodLMKM
fit(method, data, envir, verbose, ...)
# S4 method for lcMethodStratify
getName(object)
# S4 method for lcMethodStratify
getShortName(object)
# S4 method for lcMethodStratify
compose(method, envir = NULL, ...)
# S4 method for lcMethodStratify
fit(method, data, envir, verbose, ...)
# S4 method for lcModelFeature
getName(object, ...)
# S4 method for lcModelFeature
getShortName(object, ...)
# S4 method for lcModelLMKM
predictForCluster(object, newdata, cluster, what = "mu", ...)
# S3 method for lcModelLMKM
coef(object, ..., cluster = NULL)
# S4 method for lcModelLMKM
converged(object, ...)
# S4 method for lcModelLMKM
postprob(object, ...)

Arguments

object

The object to extract the label from.

method

The lcMethod object.

data

The data, as a data.frame, on which the model will be trained.

verbose

A R.utils::Verbose object indicating the level of verbosity.

...

Arguments passed on to stats::predict.lm

se.fit

A switch indicating if standard errors are required.

scale

Scale parameter for std.err. calculation.

df

Degrees of freedom for scale.

interval

Type of interval calculation. Can be abbreviated.

level

Tolerance/confidence level.

type

Type of prediction (response or model term). Can be abbreviated.

terms

If type = "terms", which terms (default is all terms), a character vector.

na.action

function determining what should be done with missing values in newdata. The default is to predict NA.

pred.var

the variance(s) for future observations to be assumed for prediction intervals. See ‘Details’.

weights

variance weights for prediction. This can be a numeric vector or a one-sided model formula. In the latter case, it is interpreted as an expression evaluated in newdata.

envir

The environment in which the lcMethod should be evaluated

newdata

Optional data.frame for which to compute the model predictions. If omitted, the model training data is used. Cluster trajectory predictions are made when ids are not specified.

cluster

The cluster name.

what

The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying what = 'mb'.

See Also

lcMethodFeature lcMethodGCKM lcMethodLMKM