Power Analysis
December 27, 2017 0 Comments
Notes: Model-Free Scoring System for Risk Prediction
October 17, 2017 0 Comments
Notes: Temporal-Difference Learning
October 12, 2017 0 Comments
Notes: Essentials of Survival Time Analysis
October 11, 2017 0 Comments
This post aims to clarify the relationship between rates and probabilities.
Notes: Stochastic Epidemic Models
October 11, 2017 0 Comments
Discuss three different methods for formulating stochastic epidemic models.
An R Package: Fit Repeated Linear Regressions
September 26, 2017 0 Comments
Repeated Linear Regressions refer to a set of linear regressions in which there are several same variables.
A Faster Algorithm for Repeated Linear Regression
September 21, 2017 0 Comments
Repeated Linear Regression means that repeat the fitting of linear regression for many times, and there are some common parts among these regressions.
Notes: Persistence of species in the face of environmental stochasticity
September 18, 2017 0 Comments
Chain-Structured Models
September 08, 2017 0 Comments
Basic Principles of Monte Carlo
September 07, 2017 0 Comments
The Applications of Monte Carlo
September 07, 2017 0 Comments
Dynamics of Helicobacter pylori Infection
September 02, 2017 0 Comments
This post is the notes of this paper.
Healthy Human Microbiome
September 02, 2017 0 Comments
This post is the notes of this paper.
Dynamics of Helicobacter pylori colonization
September 01, 2017 0 Comments
This post is the notes of this paper.
Restricted Boltzmann Machines
August 26, 2017 0 Comments
Cox Regression
August 17, 2017 0 Comments
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.
Conjugate Gradient for Regression
August 13, 2017 0 Comments
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
August 13, 2017 0 Comments
Story about P value
August 09, 2017 0 Comments
“The p value was never meant to be used the way it’s used today.” –Goodman
Poisson Regression
August 01, 2017 0 Comments
Estimate Parameters in Logistic Regression
July 30, 2017 0 Comments
SMC in Biological Problems
July 22, 2017 0 Comments
The Gibbs Sampling
July 22, 2017 0 Comments
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.
Metropolis Algorithm
July 21, 2017 0 Comments
A Bayesian Missing Data Problem
July 18, 2017 0 Comments
Model Specification
July 17, 2017 0 Comments
For a given time series, how to choose appropriate values for $p, d, q$
Growing A Polymer
July 17, 2017 0 Comments
Adaptive Importance Sampling
July 16, 2017 0 Comments
An Illustration of Importance Sampling
July 16, 2017 0 Comments
ARIMA
July 11, 2017 0 Comments
Any time series without a constant mean over time is nonstationary.