Multi-marker methods for genetic association analysis can be performed for common and low frequency SNPs to improve power. Regression models are an intuitive way to formulate multi-marker tests. In previous studies we evaluated regression-based multi-marker tests for common SNPs, and through identification of bins consisting of correlated SNPs, developed a multi-bin linear combination (MLC) tes...

Forecasting water deficit is challenging because it modulated by uncertain climate, different environmental and anthropic factors, especially in arid semi-arid northwestern China. The monthly index D at 44 sites China over 1961−2020 were calculated. key large-scale circulation indices related to screened using Pearson’s correlation (r). Subsequently, we predicted with the multi-variable linear ...

This material is compiled for the course Empirical Modelling. Sections marked with a star (∗) are not central in the courses. The main source of inspiration when writing this text has been Chapter 4 in the book ”System Identification” by Söderström and Stoica (Prentice Hall, 1989) which also may be consulted for a more thorough treatment of the material presented here. The book is available for...

Linear regression is probably the most popular model for predicting a RV Y ∈ R based on multiple RVs X1, . . . , Xd ∈ R. It predicts a numeric variable using a linear combination of variables ∑ θiXi where the combination coefficients θi are determined by minimizing the sum of squared prediction error on the training set. We use below the convention that the first variable is always one i.e., X1...

Probablistic Model: We start with the assumption that prior to starting a sequence of experiments we have a family of random variables with means that vary linearly with respect to some deterministic independent variable. That is, there exist an intercept β0 and a slope β1 such that for each value of the independent variable x, we have a random variable Y with mean β0 + β1x. We are then given p...

Genetic algorithms (GAs) are powerful heuristic search techniques that used successfully to solve problems for many different applications. Seeding the initial population is considered as first step of GAs. In this work, a new method proposed, seeding called Multi Linear Regression Based Technique (MLRBT). That divides given large scale TSP problem into smaller sub-problems and technique works ...