Estimate the relative abundance of tissue-infiltrating immune subpopulations abundances using gene expression data.

A toolkit for causal inference in experimental and observational 
    studies. Implements various simple Bayesian models including linear, 
    negative binomial, and logistic regression for impact estimation. 
    Provides functionality for randomization and checking baseline equivalence 
    in experimental designs. The package aims to simplify the process of 
    impact measurement for researchers and analysts across different fields. 
    Examples and detailed usage instructions are available at 
    <https://book.martinez.fyi>.

Implementation of the information matrix test for generalized partial credit models.

Estimate the orientation of an inertial measurement unit 
    (IMU) with a 3-axis accelerometer and a 3-axis gyroscope using a 
    complementary filter. 'imuf' takes an IMU's accelerometer and gyroscope 
    readings, time duration, its initial orientation, and a gain factor as 
    inputs, and returns an estimate of the IMU's final orientation.

Fits Bayesian hierarchical models of vaccine
    coverage by location, birth cohort, and age. Observations 
    of vaccination status (which may span cohorts, ages, and doses) are
    used to fit a latent survival-style process model that decomposes
    coverage into a lifetime propensity to vaccinate and a
    time-varying force of vaccination. Hierarchical spatial structure 
    (e.g., state, county, school) supports partial pooling via random
    effects. Models are implemented in 'Stan' and fit via 'rstan'.
    Provides helpers to validate user-supplied input data, and to predict 
    coverage from fitted models.

Computes the 'InterModel Vigorish' ('IMV'), a metric for comparing
    the predictive accuracy of two models for binary outcomes. The 'IMV' is derived
    from the expected value of a bettor using one model's predicted probabilities
    against those of a competing model, and is estimated via k-fold cross-validation.
    Methods are provided for generalized linear models, mixed-effects models ('lme4'),
    and item response theory models ('mirt'). See
    <doi:10.1371/journal.pone.0316491>.