hier_bayes_exponentialGrowth_frequency: Hierarchical Bayesian inference of cluster-wise selection...
In emvolz-phylodynamics/variantAnalysis: sarscov2 variant analysis
Description
Usage
Arguments
Value
Description
Hierarchical Bayesian inference of cluster-wise selection coefficients with a random effect corresponding to a dichotomous genotype
Usage
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hier_bayes_exponentialGrowth_frequency(
s,
iterations = 8e+06,
thin = 200,
ncpu = 4,
MINT = -Inf,
MAXT = 2020.25,
MU = 73,
minClusterSize = 10
)
Arguments
s
data frame that describes each sample, must have columns: del_introduction, sample_time, genotype
MINT
minimum sample time for including cluster
MAXT
exclude samples after this date
MU
sets time scale of process and generation time. Generation time is 1/MU years
minClusterSize
minimum size for cluster to be included in analysis
Value
Bayesian sampler output produced by BayesianTools::runMCMC
emvolz-phylodynamics/variantAnalysis documentation built on Nov. 13, 2021, 7:16 p.m.
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Description Usage Arguments Value
Description
Hierarchical Bayesian inference of cluster-wise selection coefficients with a random effect corresponding to a dichotomous genotype
Usage
1 2 3 4 5 6 7 8 9 10 | hier_bayes_exponentialGrowth_frequency(
s,
iterations = 8e+06,
thin = 200,
ncpu = 4,
MINT = -Inf,
MAXT = 2020.25,
MU = 73,
minClusterSize = 10
)
|
Arguments
s |
data frame that describes each sample, must have columns: del_introduction, sample_time, genotype |
MINT |
minimum sample time for including cluster |
MAXT |
exclude samples after this date |
MU |
sets time scale of process and generation time. Generation time is 1/MU years |
minClusterSize |
minimum size for cluster to be included in analysis |
Value
Bayesian sampler output produced by BayesianTools::runMCMC
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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