simulate_trend: Simulate trends
In ssokolen/metcourse: Tools for Metabolic Time-course Data

Underlying function for simulating different types of time-course trends. Each trend supports parameter generation from one or two sets of parameter limits.

1	simulate_trend(n, n.samples, f_trend, par1, par2 = NULL, p = 0.5)

`n`	Number of trends to generate.
`n.samples`	Number of timepoints within each trend.
`f_trend`	Function that taxes x values and a vector of parameters and generates a corresponding set of y values.
`par1`	Parameter vector of lower and upper bounds for first set of trends.
`par2`	Optional parameter vector of lower and upper bounds for second set of trends.
`p`	Proportion of trends to generate using `par1` vs. `par2`. Note, `p` is ignored if `par2` is not specified.

A dataframe with each row representing a metabolite concentration time-course scaled between 0 and 1. The corresponding x variables are assumed to be equally spaced between 0 and 1 i.e. x <- seq(0, 1, length.out=n.samples).

ssokolen/metcourse documentation built on May 30, 2019, 8:43 a.m.