Composite likelihood parameter estimate and asymptotic covariance matrix are calculated for the spatial ordinal data with replications, where spatial ordinal response with covariate and both spatial exponential covariance within subject and independent and identically distributed measurement error.  Parameter estimation can be performed by either solving the gradient function or maximizing composite log-likelihood. Parametric bootstrapping is used to estimate the Godambe information matrix and hence the asymptotic standard error and covariance matrix with parallel processing option. Moreover, the proposed surrogate residual, which extends the results of Liu and Zhang (2017) <doi: 10.1080/01621459.2017.1292915>, can act as a useful tool for model diagnostics.

Calculate the distance between single-arm observational studies using covariate information to remove heterogeneity in Network Meta-Analysis (NMA) of randomized clinical trials. Facilitate the inclusion of observational data in NMA, enhancing the comprehensiveness and robustness of comparative effectiveness research. Schmitz (2018) <doi:10.1186/s12874-018-0509-7>.

A unified interface for simplifying cloud storage interactions, 
    including uploading, downloading, reading, and writing files, with functions
    for both 'Google Drive' (<https://www.google.com/drive/>) and 'Amazon S3' 
    (<https://aws.amazon.com/s3/>).

Interface to the Google Cloud Machine Learning Platform
  <https://cloud.google.com/vertex-ai>, which provides cloud tools for training machine
  learning models.

The 'CloudOS' client library for R makes it easy to interact with 
    CloudOS in the R environment for analysis.

Access Cloudstor via their WebDAV API. This package can read, write, and navigate Cloudstor from R.

Provides means of plots for comparing utilization data of compute systems.

Computes the uniform rate of profit, the vector of price of 
    production and the vector of labor values; and also compute measures of deviation 
    between relative prices of production and relative values.  
    <https://scholarworks.umass.edu/econ_workingpaper/347/>. You provide the  
    input-output data and 'clptheory' does the calculations for you.