Choose a confidence interval for a pooled DeCovarT composition

One entry point for the interior intervals of the population convolution (covariance weights \(p_j^2\), no technical scales). The default, method = "ilr", is confint_ilr_backtransform().

ilr

Wald interval for \(\boldsymbol{\rho}\), mapped by the inverse ILR chart.

wald

Delta method on \(\boldsymbol{p}\). Endpoints can leave \([0,1]\).

firth

Wald interval at the Jeffreys-penalised estimate (fit_firth_decovart()). interval_ilr is the same estimate mapped through the inverse chart.

profile

Likelihood-ratio interval (confint_profile_decovart()). This is the interior calibration. A null on a face is lrt_decovart(), not an interval.

bootstrap

Parametric percentile interval (bootstrap_decovart()).

reference

Resample the reference, then refit (reference_bootstrap_decovart()). Two or more donors in every cell type use the donor bootstrap and keep the bulk fixed. Otherwise columns are resampled within each cell type and the bulk is regenerated. Cell-type labels are not shuffled; that check is equivariance_check_decovart().

Columns of y share one composition. fit_decovart() instead estimates a separate composition per column, and confint.decovart_fit() is the per-column delta method.

Usage

confint_decovart(
  y,
  mean_signature_matrix = NULL,
  Sigma = NULL,
  method = c("ilr", "wald", "firth", "profile", "bootstrap", "reference"),
  level = 0.95,
  p = NULL,
  n_draws = 2000L,
  n_boot = 500L,
  seed = NULL,
  reference_profiles = NULL,
  donor_ids = NULL,
  resample = NULL,
  regenerate_bulk = NULL,
  ...
)

Arguments

y

Numeric vector of length \(G\), or \(G\times N\) matrix of replicate bulk profiles that share one composition; their log-likelihoods are summed (the pooled, population-level fit).

mean_signature_matrix

Numeric matrix \(\boldsymbol{\mu}\in\mathcal{M}_{G\times J}\) (plug-in means).

Sigma

Array of cell-type covariances in \(\mathcal{M}_{G\times G\times J}\).

method

Interval to compute. See Description.

level

Confidence level.

p

Composition at which to evaluate the information. NULL uses the pooled maximum likelihood estimate.

n_draws

Monte Carlo size used when there are three or more cell types. Ignored for two cell types.

n_boot

Bootstrap size for method = "bootstrap" or "reference".

seed

Optional seed for the Monte Carlo map. The previous random-number state is restored. NULL leaves the state unchanged and draws from the current stream.

reference_profiles, donor_ids

Passed to reference_bootstrap_decovart() when method = "reference".

resample

"donors" or "cells". NULL chooses from donor_ids as in Description.

regenerate_bulk

Whether the reference bootstrap redraws the bulk. NULL follows the automatic rule in Description.

...

Passed to the selected method (epsilon, itmax, celltypes, null_value, ridge, n_replicates).

Value

A list with method, estimate and interval. Other elements depend on method.

See also

lrt_decovart(), confint_single_cell()

Other decovart_inference: bootstrap_decovart(), bootstrap_single_cell(), boundary_diagnostics(), chi_bar_square_pvalue(), confint_ilr_backtransform(), confint_profile_decovart(), confint_profile_single_cell(), confint_single_cell(), equivariance_check_decovart(), fit_firth_decovart(), fit_firth_single_cell(), lrt_decovart(), lrt_single_cell(), multistart_decovart(), reference_bootstrap_decovart(), reference_bootstrap_single_cell(), restricted_mle_decovart(), restricted_mle_single_cell()

Examples

mu <- matrix(c(20, 40, 15, 40, 20, 25), nrow = 3)
colnames(mu) <- paste0("ct", 1:2)
Sigma <- array(c(diag(3), diag(3)), dim = c(3, 3, 2))
y <- drop(mu %*% c(0.6, 0.4))
confint_decovart(y, mu, Sigma)$interval
#>          2.5%     97.5%
#> ct1 0.5514710 0.6453814
#> ct2 0.3546186 0.4485290
confint_decovart(y, mu, Sigma, method = "wald")$interval
#>          2.5%     97.5%
#> ct1 0.5522501 0.6464257
#> ct2 0.3535743 0.4477499