WeiYa's Work Yard

Notes: Essentials of Survival Time Analysis

This post aims to clarify the relationship between rates and probabilities.

Notes: Stochastic Epidemic Models

Discuss three different methods for formulating stochastic epidemic models.

An R Package: Fit Repeated Linear Regressions

Repeated Linear Regressions refer to a set of linear regressions in which there are several same variables.

A Faster Algorithm for Repeated Linear Regression

Repeated Linear Regression means that repeat the fitting of linear regression for many times, and there are some common parts among these regressions.

Dynamics of Helicobacter pylori Infection

This post is the notes of this paper.

Healthy Human Microbiome

This post is the notes of this paper.

Dynamics of Helicobacter pylori colonization

This post is the notes of this paper.

Cox Regression

Survival analysis examines and models the time it takes for events to occur. It focuses on the distribution of survival times. There are many well known methods for estimating unconditional survival distribution, and they examines the relationship between survival and one or more predictors, usually terms covariates in the survival-analysis literature. And Cox Proportional-Hazards regression model is one of the most widely used method of survival analysis.

The conjugate gradient method is an iterative method for solving a linear system of equations, so we can use conjugate method to estimate the parameters in (linear/ridge) regression.

Bayesian Estimation for Linear Regression

“The p value was never meant to be used the way it’s used today.” –Goodman

The Gibbs Sampling

The Gibbs sampler is a special MCMC scheme. Its most prominent feature is that the underlying Markov chain is constructed by composing a sequence of conditional distributions along a set of directions.

Model Specification

For a given time series, how to choose appropriate values for $p, d, q$