Implements methods to normalize multiplexed imaging data, including
    statistical metrics and visualizations to quantify technical variation in 
    this data type. Reference for methods listed here: Harris, C., Wrobel, J., 
    & Vandekar, S. (2022). mxnorm: An R Package to Normalize Multiplexed Imaging 
    Data. Journal of Open Source Software, 7(71), 4180, 
    <doi:10.21105/joss.04180>.

Provides a 'lavaan'-like syntax for 'OpenMx' models. The syntax supports 
  definition variables, bounds, and parameter transformations. This allows for
  latent growth curve models with person-specific measurement occasions, moderated
  nonlinear factor analysis and much more.

The stepwise variable selection procedure (with iterations
 between the 'forward' and 'backward' steps) can be used to obtain
 the best candidate final regression model in regression analysis.
 All the relevant covariates are put on the 'variable list' to be
 selected. The significance levels for entry (SLE) and for stay
 (SLS) are usually set to 0.15 (or larger) for being conservative.
 Then, with the aid of substantive knowledge, the best candidate
 final regression model is identified manually by dropping the
 covariates with p value > 0.05 one at a time until all regression
 coefficients are significantly different from 0 at the chosen alpha
 level of 0.05.

The chi-squared test for goodness of fit 
    and independence test.

Handling the microclimatic data in R. The 'myClim' workflow begins
    at the reading data primary from microclimatic dataloggers,
    but can be also reading of meteorological station data from files.
    Cleaning time step, time zone settings and metadata collecting is the next step of the work flow.
    With 'myClim' tools one can crop, join, downscale, and convert microclimatic data formats, sort them into localities,
    request descriptive characteristics and compute microclimatic variables.
    Handy plotting functions are provided with smart defaults.

The mycobacrvR package contains utilities to provide detailed information for B cell and T cell epitopes for predicted adhesins from various servers such as ABCpred, Bcepred, Bimas, Propred, NetMHC and IEDB. Please refer the URL below to download data files (data_mycobacrvR.zip) used in functions of this package.