Description Usage Arguments Value
View source: R/param_mat_function.R
Generate matrix with all combinations of parameters for NT simulation
1 2 | param_mat(Nmeta, ps = 1, r = 1, m, Nlocal, nOTU, n, Nmeta_sd, Nlocal_sd,
num_k, sourc)
|
Nmeta |
vector of values to be used in simulations: number of reads in meta community samples to be used in simulations |
ps |
vector of values to be used in simulations: this parameter adjusts the amount of variation between samples, with a range between 0 and 1. This value is the probability that a given OTU's relative abundance with be permuted in a sample. Values of 0 result in homologous taxa abundance distributions across all samples. Default in 1. |
r |
vector of values to be used in simulations: this parameter adjusts the amount of variation between samples. Values can range from 0 to 1. r = 0 will result in a uniformly distributed relative abundance distribution within a sample. |
m |
vector of values to be used in simulations: true parameter values |
Nlocal |
vector of values to be used in simulations: number of reads in local community samples |
nOTU |
vector of values to be used in simulations: number of OTUs |
n |
vector of values to be used in simulations: number of samples |
Nmeta_sd |
vector of values to be used in simulations: this parameter adjusts the amount of variation in the number of reads in meta community samples. Specifically, this value is the standard deviation used in a normal distribution with mean Nmeta from which samples sizes are generated |
Nlocal_sd |
vector of values to be used in simulations: this parameter adjusts the amount of variation in the number of reads in local community samples. Specifically, this value is the standard deviation used in a normal distribution with mean Nlocal from which samples sizes are generated from. |
num_k |
a single value for the number of simulations to run for each set of parameters |
a matrix of all combinations of parameters, except for combinations where the number of reads in the local community samples is larger than the number of reads in the meta community samples.
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