deprecated-matrixCorr: Deprecated Compatibility Wrappers
In matrixCorr: Collection of Correlation and Association Estimators

deprecated-matrixCorr

R Documentation

Deprecated Compatibility Wrappers

Description

Temporary wrappers for functions renamed in matrixCorr 1.0.0. These wrappers preserve the pre-1.0 entry points while warning that they will be removed in 2.0.0.

Usage

bland_altman(
  group1,
  group2,
  two = 1.96,
  mode = 1L,
  conf_level = 0.95,
  n_threads = getOption("matrixCorr.threads", 1L),
  verbose = FALSE
)

bland_altman_repeated(
  data = NULL,
  response,
  subject,
  method,
  time,
  two = 1.96,
  conf_level = 0.95,
  n_threads = getOption("matrixCorr.threads", 1L),
  include_slope = FALSE,
  use_ar1 = FALSE,
  ar1_rho = NA_real_,
  max_iter = 200L,
  tol = 1e-06,
  verbose = FALSE
)

biweight_mid_corr(
  data,
  c_const = 9,
  max_p_outliers = 1,
  pearson_fallback = c("hybrid", "none", "all"),
  na_method = c("error", "pairwise"),
  mad_consistent = FALSE,
  w = NULL,
  sparse_threshold = NULL,
  n_threads = getOption("matrixCorr.threads", 1L),
  output = c("matrix", "sparse", "edge_list"),
  threshold = 0,
  diag = TRUE
)

distance_corr(data, na_method = c("error", "pairwise"), ...)

partial_correlation(
  data,
  method = c("oas", "ridge", "sample"),
  lambda = 0.001,
  return_cov_precision = FALSE,
  ci = FALSE,
  conf_level = 0.95,
  output = c("matrix", "sparse", "edge_list"),
  threshold = 0,
  diag = TRUE
)

ccc_lmm_reml(
  data,
  response,
  rind,
  method = NULL,
  time = NULL,
  interaction = FALSE,
  max_iter = 100,
  tol = 1e-06,
  Dmat = NULL,
  Dmat_type = c("time-avg", "typical-visit", "weighted-avg", "weighted-sq"),
  Dmat_weights = NULL,
  Dmat_rescale = TRUE,
  ci = FALSE,
  conf_level = 0.95,
  ci_mode = c("auto", "raw", "logit"),
  verbose = FALSE,
  digits = 4,
  use_message = TRUE,
  ar = c("none", "ar1"),
  ar_rho = NA_real_,
  slope = c("none", "subject", "method", "custom"),
  slope_var = NULL,
  slope_Z = NULL,
  drop_zero_cols = TRUE,
  vc_select = c("auto", "none"),
  vc_alpha = 0.05,
  vc_test_order = c("subj_time", "subj_method"),
  include_subj_method = NULL,
  include_subj_time = NULL,
  sb_zero_tol = 1e-10
)

ccc_pairwise_u_stat(
  data,
  response,
  method,
  subject,
  time = NULL,
  Dmat = NULL,
  delta = 1,
  ci = FALSE,
  conf_level = 0.95,
  n_threads = getOption("matrixCorr.threads", 1L),
  verbose = FALSE
)

Arguments

`group1`, `group2`	Numeric vectors of equal length.
`two`	Positive scalar; the multiple of the standard deviation used to define the limits of agreement.
`mode`	Integer; 1 uses `group1 - group2`, 2 uses `group2 - group1`.
`conf_level`	Confidence level.
`n_threads`	Integer number of OpenMP threads.
`verbose`	Logical; print brief progress or diagnostic output.
`data`	A `data.frame`, matrix, or repeated-measures dataset accepted by the corresponding replacement function.
`response`	Numeric response vector or column name, depending on the target method.
`subject`	Subject identifier or subject column name.
`method`	Method label or method column name.
`time`	Replicate/time index or time column name.
`include_slope`	Logical; whether to estimate proportional bias.
`use_ar1`	Logical; whether to use AR(1) within-subject correlation.
`ar1_rho`	AR(1) parameter.
`max_iter`, `tol`	EM control parameters.
`c_const`	Positive numeric Tukey biweight tuning constant.
`max_p_outliers`	Numeric in `⁠(0, 1]⁠`; optional cap on the maximum proportion of outliers on each side.
`pearson_fallback`	Character fallback policy used by `bicor()`.
`na_method`	Missing-data policy forwarded to the replacement function when supported.
`mad_consistent`	Logical; if `TRUE`, uses the consistency-corrected MAD.
`w`	Optional vector of case weights.
`sparse_threshold`	Optional threshold controlling sparse output.
`output`	Output representation for the computed estimates.
`threshold`	Non-negative absolute-value filter for non-matrix outputs.
`diag`	Logical; whether to include diagonal entries in non-matrix outputs.
`...`	Additional arguments forwarded to the replacement function when supported.
`lambda`	Numeric regularisation strength used by `pcorr()`.
`return_cov_precision`	Logical; if `TRUE`, also return covariance and precision matrices.
`ci`	Logical; if `TRUE`, request confidence intervals when supported by the replacement function.
`rind`	Character; column identifying subjects, forwarded as `subject` to `ccc_rm_reml()`.
`interaction`	Logical; forwarded to `ccc_rm_reml()`.
`Dmat`	Optional distance matrix forwarded to `ccc_rm_reml()`.
`Dmat_type`	Character selector controlling how `Dmat` is constructed.
`Dmat_weights`	Optional weights used when `Dmat_type` requires them.
`Dmat_rescale`	Logical; whether to rescale `Dmat`.
`ci_mode`	Character selector for the confidence-interval scale used by `ccc_rm_reml()`.
`digits`	Display precision forwarded to `ccc_rm_reml()`.
`use_message`	Logical; whether the deprecated wrapper emits a lifecycle message.
`ar`	Character selector for the within-subject residual correlation model.
`ar_rho`	Numeric AR(1) parameter.
`slope`	Character selector for the proportional-bias slope structure.
`slope_var`	Optional covariance matrix for custom slopes.
`slope_Z`	Optional design matrix for custom slopes.
`drop_zero_cols`	Logical; whether zero-variance design columns are dropped.
`vc_select`	Character selector controlling variance-component selection.
`vc_alpha`	Significance level used in variance-component selection.
`vc_test_order`	Character vector controlling the variance-component test order.
`include_subj_method`	Optional logical override for the subject-by-method component.
`include_subj_time`	Optional logical override for the subject-by-time component.
`sb_zero_tol`	Numerical tolerance used when stabilising the scale-bias term.
`delta`	Numeric power exponent for U-statistics distances.