deprecated-matrixCorr: 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,
  verbose = FALSE
)
bland_altman_repeated(
  data = NULL,
  response,
  subject,
  method,
  time,
  two = 1.96,
  conf_level = 0.95,
  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)
)
distance_corr(data, check_na = TRUE)
partial_correlation(
  data,
  method = c("oas", "ridge", "sample"),
  lambda = 0.001,
  return_cov_precision = FALSE,
  ci = FALSE,
  conf_level = 0.95
)
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.
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 used by bicor().
mad_consistent: Logical; if TRUE, uses the consistency-corrected MAD.
w: Optional vector of case weights.
sparse_threshold: Optional threshold controlling sparse output.
n_threads: Integer number of OpenMP threads.
check_na: Logical validation flag used by dcor().
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 for 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.

Details

Renamed functions:

bland_altman() -> ba()
bland_altman_repeated() -> ba_rm()
biweight_mid_corr() -> bicor()
distance_corr() -> dcor()
partial_correlation() -> pcorr()
ccc_lmm_reml() -> ccc_rm_reml()
ccc_pairwise_u_stat() -> ccc_rm_ustat()

The deprecated wrappers will be removed in matrixCorr 2.0.0.