CDM — CDM-utilities" />
CDM-utilities.Rd
Utility functions in CDM.
## 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(...)
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,
|
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 |
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 |