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Zhen Zhang's Projects

aft_bayes_lasso icon aft_bayes_lasso

Zhang, Z., Sinha, S., Maiti, T., and Shipp, E. (2016) Bayesian variable selection in the AFT model with an application to the SEER breast cancer data. Statistical Methods in Medical Research.

agreeordinal icon agreeordinal

Evaluate the agreement between two raters on ordinal scale for classification. See Giri, S., Nejadhashemi, A. P., Woznicki, S. A. and Zhang, Z. (2014). Analysis of best management practice effectiveness and spatiotemporal variability based on different targeting strategies. Hydrological Processes. 28(3), 431-445.

bayesdynamicendo icon bayesdynamicendo

A Bayesian dynamic model with semi-varying coefficients for heterogeneity and endogeneity of time-dependent covariates for cross-sectional data in marketing science.

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Bayesian Spatio-temporal model with separable CAR-AR covariance structure in "Bayesian Regression and Neuro Fuzzy Methods Reliability Assessment for Estimating Streamflow". Water. 8(7), 287.

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MATALAB code for "Clustering Curves Based on Change Point Analysis: A Nonparametric Bayesian Approach", Statistica Sinica

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Codes for Reinisch, W., Pradhan, V., Saira, A., Zhang, Z. and Gale, J. (2023). Alternative endoscopy reading paradigms determine score reliability and effect size in ulcerative colitis. Journal of Crohn’s and Colitis.

lpa_rmplus icon lpa_rmplus

Latent profile analysis using R and Mplus based on the procedure described in: Passalacqua, N. V., Zhang, Z. and Pierce, S. J. (2013). Sex determination of human skeletal populations using latent profile analysis, American Journal of Physical Anthropology, 151 (4), 538-543.

machinelearn icon machinelearn

Some codes for machine learning algorithms used for papers with various collaborators.

metazip icon metazip

Meta-analysis of rare event using zero-inflated Poisson model.

midi2roll2gif icon midi2roll2gif

MATLAB toolkit to convert nusic MIDI file to GIF animation pianoroll. This function is based on the MATLAB MIDI toolbox.

mixprop icon mixprop

Bayesian Mixed Proportional odds model (ordinal response) and Bayesian mixed beta regression (bounded response). Codes originally developed for Zhang, Z., with Calantone, R. J., Lim, C. and Maiti, T. (2016). Ranking Product Lines using Customer's Brand Ratings: Application of a Bayesian proportional odds model.

mrv icon mrv

Median Regression model with Varying coefficients

multicar icon multicar

Multi-resolution CAR model for spatial areal data in "Evaluating Stream Health Based Environmental Justice Model Performance at Different Spatial Scales". Journal of Hydrology.

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k-Nearest Neighbor Diagnostic Tools

pccat icon pccat

PCCAT (Principle Component and Clustering Analysis Tool) is an add-on module for R designed for Michigan Department of Environmental Quality (MDEQ) clients via Center for Statistical Training and Consulting (CSTAT). It is mainly designed for multivariate environmental data analysis. Based on statistical software R functions and packages, it consists of four main steps: pre-processing, visualization, principle component analysis and clustering analysis. It has been designed to be user-friendly with graphic output and user prompts to take advantage of the many useful functions and packages coded in R, combined with Excel for data analysis.

porferanalysis icon porferanalysis

Spatio-temporal analysis for fertility rates in Portugal, including STM/SFC code & demo data in our paper in Journal of Official Statistics.

sfc icon sfc

Spatio-functional clustering (SFC) of spatial/temporal/functional objects.

spbvs icon spbvs

Bayesian variable selection for spatial areal data with Conditional Autoregressive (CAR) model for Gaussian and Poisson response. Developed for a series of environmental&ecological studies.

spdynampois icon spdynampois

Spatial Dynamic Poisson regression developed for "Regional-based mitigation to reduce wildlife-vehicle collisions". Journal of Wildlife Management and Wildlife Monographs.

tsste icon tsste

R/MATLAB/C code for "Two-Sample Smooth Tests for the Equality of Distributions in One and Higher Dimensions". Bernoulli. 23, 951-989.

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