santaR_CBand: Compute Group Mean Curve Confidence Bands

In santaR: Short Asynchronous Time-Series Analysis

Compute Group Mean Curve Confidence Bands

Description

Generate bootstrapped group mean curve Confidence Bands, by resampling of individual curves with replacement. Returns a SANTAObj with added Confidence Bands.

• Resampling whole data curves assumes less of the data than resampling of residuals.

• The resampled distribution is of same size as the original distribution (same number of individuals in each group as in the input data).

• The degree of freedom for the estimator is identical to the one employed for curve fitting in santaR_fit.

Usage

santaR_CBand(SANTAObj, nBoot = 1000, alpha = 0.05, subsampling = 250)

Arguments

SANTAObj	A fitted SANTAObj as generated by santaR_fit.
nBoot	(int) Number of bootstrapping rounds. Default 1000.
alpha	(float) Confidence (0.05 for 95% Confidence Bands). Default 0.05.
subsampling	(int) Number of points to sample in the time range (for the estimator and Confidence Bands). Default is 250.

Value

A SANTAObj with added Confidence Bands for each group.

See Also

Other Analysis: get_grouping(), get_ind_time_matrix(), santaR_auto_fit(), santaR_auto_summary(), santaR_fit(), santaR_plot(), santaR_pvalue_dist(), santaR_pvalue_fit(), santaR_start_GUI()

Examples

## 56 measurements, 8 subjects, 7 unique time-points
## Default parameter values decreased to ensure an execution < 2 seconds
Yi          <- acuteInflammation$data$var_3
ind         <- acuteInflammation$meta$ind
time        <- acuteInflammation$meta$time
group       <- acuteInflammation$meta$group
grouping    <- get_grouping(ind, group)
inputMatrix <- get_ind_time_matrix(Yi, ind, time)
SANTAObj    <- santaR_fit(inputMatrix, df=5, grouping=grouping, verbose=TRUE)
SANTAObj    <- santaR_CBand(SANTAObj, nBoot=100)

santaR documentation built on May 24, 2022, 1:06 a.m.