curveFitting: Fit longitudinal data
In MetaLonDA: Metagenomics Longitudinal Differential Abundance Method

Description Usage Arguments Value References Examples

Fits longitudinal samples from the same group using negative binomial smoothing splines or LOWESS

1	curveFitting(df, method = "nbinomial", points)

`df`	dataframe has the Count, Group, ID, Time
`method`	fitting method (nbinomial, lowess)
`points`	points at which the prediction should happen

returns the fitted model

Ahmed Metwally (ametwall@stanford.edu)

data(metalonda_test_data)
n.sample = 5 
n.timepoints = 10 
n.group = 2 
Group = factor(c(rep(0, n.sample*n.timepoints), rep(1, n.sample*n.timepoints)))
Time = rep(rep(1:n.timepoints, times = n.sample), 2)
ID = factor(rep(1:(2*n.sample), each = n.timepoints))
points = seq(1, 10, length.out = 10)
aggretage.df = data.frame(Count = metalonda_test_data[1,], Time = Time, Group = Group, ID = ID)
cf = curveFitting(df = aggretage.df, method= "nbinomial", points)