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R code, simulations, and modeling

Blog posts by Stefan Gelissen

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R code for fitting a mixture distribution to censored data
R code for fitting a three-parameter Weibull distribution
R code for implementing an Ensemble Kalman Filter
R code for modeling with left truncated and right/interval censored data
R code for Martingale residuals of a parametric survival model
Extreme value analysis in engineering (largest extreme values)
R code for implementing a particle filter

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state space model nonlinear dynamic model nonlinear Kalman filtering likelihood based confidence intervals censored observations quantiles copulas temporal data parametric survival model forecasting NHPP lognormal distribution Weibull distribution AFT model bootstrap method

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Implementing a particle filter in C++ using Rcpp (part 2)
Implementing a particle filter in C++ using Rcpp (part 1)
R code for fitting a model to unbalanced longitudinal data with a copula
R code for fitting a model to longitudinal data with a copula

Tag: backward-simulation particle smoother

R code for implementing the backward-simulation particle smoother

The following R code implements the backward-simulation particle smoother in R.

Backward-simulation particle smoother

Continue reading R code for implementing the backward-simulation particle smoother

Posted on April 11, 2016Tags backward-simulation particle smoother, nonlinear dynamic model, state space model

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