jointfun: Construct distribution using different parameter combinations
In ruy204/FiTnEss: FiTnEss: Finding TnSeq Essential Genes
Description
Usage
Arguments
Examples
Description
For each pair of parameters, this function constructs theoretical distributions which could be used in my_cvm function to identify optimized parameters.
Usage
1
Arguments
data_input
vector of data input to help fit parameters
lambda
proportion of non-essential genes/whole genes
lp
parameter for negative binomial distribution
sigma
parameter for negative binomial distribution
nta
number of TA sites in gene
Examples
1
2
3
4
jointfun(data_vector,0.7,5,0,5,10)
{ ~fit_distribution }
ruy204/FiTnEss documentation built on Jan. 23, 2021, 2:52 a.m.
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Description Usage Arguments Examples
Description
For each pair of parameters, this function constructs theoretical distributions which could be used in my_cvm function to identify optimized parameters.
Usage
1 |
Arguments
data_input |
vector of data input to help fit parameters |
lambda |
proportion of non-essential genes/whole genes |
lp |
parameter for negative binomial distribution |
sigma |
parameter for negative binomial distribution |
nta |
number of TA sites in gene |
Examples
1 2 3 4 | jointfun(data_vector,0.7,5,0,5,10)
{ ~fit_distribution }
|
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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