Xiaofei Wang

Xiaofei Wang

4 packages on CRAN

atus

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Abridged data from the American Time Use Survey (ATUS) for years 2003-2016. The ATUS is an annual survey conducted on a sample of individuals across the United States studying how individuals spent their time over the course of a day. Individual respondents were interviewed about what activities they did, during what times (rounded to 15 minute increments), at what locations, and in the presence of which individuals. The activities are subsequently encoded based on 3 separate tier codes for classification. This package includes data from the multi-year ATUS Activities, ATUS-CPS, and ATUS Respondents files were included. Columns were selected based on completeness of data as well as presence on the Frequently Used Variables list provided by the ATUS website. All activity codes (other than code '50' for 'Unable to Code') were included. Permission was obtained from the Bureau of Labor Statistics for inclusion in this package. The full data can be obtained from <http://www.bls.gov/tus/>.

bcp

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Provides an implementation of the Barry and Hartigan (1993) product partition model for the normal errors change point problem using Markov Chain Monte Carlo. It also extends the methodology to regression models on a connected graph (Wang and Emerson, 2015); this allows estimation of change point models with multivariate responses. Parallel MCMC, previously available in bcp v.3.0.0, is currently not implemented.

fc

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Provides a streamlined, standard evaluation-based approach to multivariate function composition. Allows for chaining commands via a forward-pipe operator, %>%.

intcensROC

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The kernel of this 'Rcpp' based package is an efficient implementation of the generalized gradient projection method for spline function based constrained maximum likelihood estimator for interval censored survival data (Wu, Yuan; Zhang, Ying. Partially monotone tensor spline estimation of the joint distribution function with bivariate current status data. Ann. Statist. 40, 2012, 1609-1636 <doi:10.1214/12-AOS1016>). The key function computes the density function of the joint distribution of event time and the marker and returns the receiver operating characteristic (ROC) curve for the interval censored survival data as well as area under the curve (AUC).