CDM-utilities {CDM}

Utility Functions in CDM

Description

Utility functions in CDM.

Usage

## requireNamespace with package message for needed installation
CDM_require_namespace(pkg)
## attach internal function in a package
cdm_attach_internal_function(pack, fun)

## print function in summary
cdm_print_summary_data_frame(obji, from=NULL, to=NULL, digits=3, rownames_null=FALSE)
## print summary call
cdm_print_summary_call(object, call_name="call")
## print computation time
cdm_print_summary_computation_time(object, time_name="time", time_start="s1",
         time_end="s2")

## string vector of matrix entries
cdm_matrixstring( matr, string )

## mvtnorm::rmvnorm with vector conversion for n=1
CDM_rmvnorm(n, mean=NULL, sigma, ...)
## fit univariate and multivariate normal distribution
cdm_fit_normal(x, w)

## fit unidimensional factor analysis by unweighted least squares
cdm_fa1(Sigma, method=1, maxit=50, conv=1E-5)

## another rbind.fill implementation
CDM_rbind_fill( x, y )
## fills a vector row-wise into a matrix
cdm_matrix2( x, nrow )
## fills a vector column-wise into a matrix
cdm_matrix1( x, ncol )

## SCAD thresholding operator
cdm_penalty_threshold_scad(beta, lambda, a=3.7)
## lasso thresholding operator
cdm_penalty_threshold_lasso(val, eta )
## ridge thresholding operator
cdm_penalty_threshold_ridge(beta, lambda)
## elastic net threshold operator
cdm_penalty_threshold_elnet( beta, lambda, alpha )
## SCAD-L2 thresholding operator
cdm_penalty_threshold_scadL2(beta, lambda, alpha, a=3.7)
## truncated L1 penalty thresholding operator
cdm_penalty_threshold_tlp( beta, tau, lambda )
## MCP thresholding operator
cdm_penalty_threshold_mcp(beta, lambda, a=3.7)

## general thresholding operator for regularization
cdm_parameter_regularization(x, regular_type, regular_lam, regular_alpha=NULL,
         regular_tau=NULL )
## values of penalty function
cdm_penalty_values(x, regular_type, regular_lam, regular_tau=NULL,
       regular_alpha=NULL)
## thresholding operators regularization
cdm_parameter_regularization(x, regular_type, regular_lam, regular_alpha=NULL,
       regular_tau=NULL)

## utility functions for P-EM acceleration
cdm_pem_inits(parmlist)
cdm_pem_inits_assign_parmlist(pem_pars, envir)
cdm_pem_acceleration( iter, pem_parameter_index, pem_parameter_sequence, pem_pars,
      PEM_itermax, parmlist, ll_fct, ll_args, deviance.history=NULL )
cdm_pem_acceleration_assign_output_parameters(res_ll_fct, vars, envir, update)

## approximation of absolute value function and its derivative
abs_approx(x, eps=1e-05)
abs_approx_D1(x, eps=1e-05)

## information criteria
cdm_calc_information_criteria(ic)
cdm_print_summary_information_criteria(object, digits_crit=0, digits_penalty=2)

## string pasting
cat_paste(...)

Arguments

pkg

An R package

pack

An R package

fun

An R function

obji

Object

from

Integer

to

Integer

digits

Number of digits used for printing

rownames_null

Logical

call_name

Character

time_name

Character

time_start

Character

time_end

Character

matr

Matrix

string

String

object

Object

n

Integer

mean

Mean vector or matrix if separate means for cases are provided. In this case, n can be missing.

sigma

Covariance matrix

...

More arguments to be passed (or a list of arguments)

x

Matrix or vector

y

Matrix or vector

w

Vector of sampling weights

nrow

Integer

ncol

Integer

Sigma

Covariance matrix

method

Method 1 indicates estimation of different item loadings, method 2 estimation of same item loadings.

maxit

Maximum number of iterations

conv

Convergence criterion

beta

Numeric

lambda

Regularization parameter

alpha

Regularization parameter

a

Parameter

tau

Regularization parameter

val

Numeric

eta

Regularization parameter

regular_type

Type of regularization

regular_lam

Regularization parameter \lambda

regular_tau

Regularization parameter \tau

regular_alpha

Regularization parameter \alpha

parmlist

List containing parameters

pem_pars

Vector containing parameter names

envir

Environment

update

Logical

iter

Iteration number

pem_parameter_index

List with parameter indices

pem_parameter_sequence

List with updated parameter sequence

PEM_itermax

Maximum number of iterations for PEM

ll_fct

Name of log-likelihood function

ll_args

Arguments of log-likelihood function

deviance.history

Deviance history, a data frame.

res_ll_fct

Result of maximized log-likelihood function

vars

Vector containing parameter names

eps

Numeric

ic

List

digits_crit

Integer

digits_penalty

Integer