A multiple testing procedure for clustered alternative hypotheses. 
    It is assumed that the p-values under the null hypotheses follow U(0,1) and 
    that the distributions of p-values from the alternative hypotheses are 
    stochastically smaller than U(0,1). By aggregating information, this 
    method is more sensitive to detecting signals of low magnitude than 
    standard methods. Additionally, sporadic small p-values appearing 
    within a null hypotheses sequence are avoided by averaging on the 
    neighboring p-values.

Change point tests for joint distributions and copulas using pseudo-observations with multipliers or bootstrap. The processes used here have been defined in Bucher, Kojadinovic, Rohmer & Segers <doi:10.1016/j.jmva.2014.07.012> and Nasri & Remillard <doi:10.1016/j.jmva.2019.03.002>.

Changing the name of an existing R package is annoying but common task especially in the early stages of package development. This package (mostly) automates this task.

Estimation of changepoints using an "S-curve"
   approximation. Formation of confidence intervals for changepoint
   locations and magnitudes. Both abrupt and gradual changes can be
   modeled.

Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.

Shiny Web Application for the Multichannel Attribution Problem. It is a user-friendly graphical interface for package 'ChannelAttribution'.

Adjusts the loglikelihood of common econometric models for
    clustered data based on the estimation process suggested in 
    Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, using the 'chandwich' 
    package <https://cran.r-project.org/package=chandwich>, and provides 
    convenience functions for inference on the adjusted models.