Package index • power.nb

All functions

contour_plot_fun(): Contour plot for showing predicted power
countdata_sim_fun(): Simulate Count Data for Microbiome Studies
deseq_fun_est(): Fold change and p-value estimations for simulations
deseqfun(): Estimate log fold changes using DESeq2.
dispersion_fit(): Fit the non-linear function to dispersion estimates
dispersion_fun(): Calculate Dispersion for Microbiome Data
dnormmix(): Density of a Normal Mixture Model
dnormmix0(): Density function for the mixture of Gaussian distributions
filter_low_count(): Filter to remove low abundant taxa
gam_fit(): Title
gen_parnames(): Generate Parameter Names for Mixture Model
genmixpars(): generate normal mixture parameters (prob vector, mean vector, sd vector for a specified set of 'x' values (logmean)
logfoldchange_fit(): Fit a mixture of Gaussian distributions to log fold change
logfoldchange_sim_fun(): Simulate Log Fold Change Values
logmean_fit(): Fit a mixture of Gaussian Distributions to log mean count of taxa.
logmean_sim_fun(): Simulate Log Means for OTUs
myrnormmix(): Simulating from a mixture of Gaussian
nllfun(): Objective function
optimal.comp(): Computes the optimal number of gaussian components for log mean count
polyfun(): General-purpose log-likelihood function, vectorized sum(pars*x^i)
power_fun_ss(): Fit a smooth power model for sample size estimation
read_data(): Extract specified data from a list of datasets
rnormmix0(): general-purpose normal-mixture deviate generator: takes matrices of probabilities, means, sds
sample_size_ss_interp(): Estimate sample size required to achieve a target statistical power
ss_solver(): Solve for the sample size required to achieve a target statistical power
uniroot_ss(): Sample Size estimation function using uniroot