F_MC_powerCircadian_outlier: F-statistics-based Monte-Carlo Circadian Power Calculation...

In weiiizong/powerCircadian: An R package for circadian data power calculation

Description

Monte-Carlo circadian power calculation based on F-statistics when outliers exist.

Usage

F_MC_powerCircadian_outlier(
  B_MC = 10000,
  n,
  A,
  sigma,
  outlier.perc = 0.05,
  phi = 0,
  period = 24,
  C = 10,
  cts = NULL,
  alpha = 0.05
)

Arguments

B_MC	Numer of Monte-Carlo simulations. Default is 10000.
n	Sample size.
A	Amplitude of the sine curve: A * sin(2π/period * (phi + cts)) + C.
sigma	\sigma in the independent Normal error term N(0,σ).
outlier.perc	The percentage of outlying samples. Default is 0.05.
phi	Phase of the sine curve. Default is 0.
period	Period of the sine curve. Default is 24.
C	Offset of the sine curve. Default is 10.
cts	Circadian time design vector.
alpha	Type I error control. Default is 0.05.

Details

Calculate power of circaidan data from Monte-Carlo simulated data when outliers exist.

Value

A vector of empirical type I error and Monte-Carlo power based on F-statistics.

Author(s)

Wei Zong, Zhiguang Huo

Examples

B_MC = 10000
n = 100
cts = seq(0,24,length.out = n+1)[-1]
A = 1
sigma = 1
phi = 0
C = 10
outlier.perc = 0.05
F_MC_powerCircadian_outlier(B_MC, n, A, sigma, outlier.perc, phi, period = 24, C=10, cts,
alpha = 0.05)

weiiizong/powerCircadian documentation built on Dec. 23, 2021, 5:09 p.m.