Probability Distribution Methods to Predict Stock Profits

Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...
GitHub

Variable Selection Using Random Forests

R package, implementing a three steps variable selection procedure based on random forests. Initially developed to handle high dimensional data (for which number of variables largely exceeds number of ...
eLife

Association between continuous glucose monitoring-derived metrics and coronary plaque vulnerability: A retrospective exploratory analysis

The mean, variance, and autocorrelation of glucose dynamics are independently associated with coronary plaque vulnerability.
IEEE

Downscaling Land Surface Temperatures Using a Random Forest Regression Model With Multitype Predictor Variables

Abstract: In this paper, a random forest regression model with multitype predictor variables (MTVRF) was utilized with four kinds of input variables, including surface reflectance, spectral indices, ...
BMJ

Cycling and cardiovascular disease risk factors including body composition, blood lipids and cardiorespiratory fitness analysed as continuous variables: Part 2—systematic ...

Objectives We aimed to examine the relationship between cycling (particularly commuter cycling) and risk factors associated with cardiovascular diseases (CVDs) including body composition, blood lipids ...
GitHub

Continuous Analysis BrainArray CustomCDF Example

This is a sample repository showing a Continuous Analysis Workflow for RNA-Seq analysis. A description of continuous analysis is available as a pre-print. In this example we evaluate the effect of ...
IEEE

Novel Methods to Construct Empirical CDF for Continuous Random Variables using Censor Data

Abstract: We deal with the problem of creating empirical CDF (ECDF) for a continuous random variable X, defined as time of an event of interest, such as failure or repair. The data sample to construct ...