Utility Functions in CDM
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 λ |
regular_tau |
Regularization parameter τ |
regular_alpha |
Regularization parameter α |
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 |
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.