Analysis of genetic marker-phenotype relationships by jack-knifed partial least squares regression (PLSR)

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Partial Least Squares Regression (PLS)

Number of latents The same number of factors will be extracted for PLS responses as for PLS factors. The researcher must specify how many latents to extract (in SPSS the default is 5). There is no one criterion for deciding how many latents to employ. Common alternatives are: 1. Cross-validating the model with increasing numbers of factors, then choosing the number with minimum prediction error...

متن کامل

Partial Least Squares (PLS) Regression

Pls regression is a recent technique that generalizes and combines features from principal component analysis and multiple regression. It is particularly useful when we need to predict a set of dependent variables from a (very) large set of independent variables (i.e., predictors). It originated in the social sciences (specifically economy, Herman Wold 1966) but became popular first in chemomet...

متن کامل

Partial least squares methods: partial least squares correlation and partial least square regression.

Partial least square (PLS) methods (also sometimes called projection to latent structures) relate the information present in two data tables that collect measurements on the same set of observations. PLS methods proceed by deriving latent variables which are (optimal) linear combinations of the variables of a data table. When the goal is to find the shared information between two tables, the ap...

متن کامل

Mean squared error of prediction (MSEP) estimates for principal component regression (PCR) and partial least squares regression (PLSR)∗

The paper presents results from simulations based on real data, comparing several competing mean squared error of prediction (MSEP) estimators on principal components regression (PCR) and partial least squares regression (PLSR): leave-one-out crossvalidation, K-fold and adjusted K-fold cross-validation, the ordinary bootstrap estimate, the bootstrap smoothed cross-validation (BCV) estimate and ...

متن کامل

Robust Methods for Partial Least Squares Regression

Partial Least Squares Regression (PLSR) is a linear regression technique developed to deal with high-dimensional regressors and one or several response variables. In this paper we introduce robustified versions of the SIMPLS algorithm being the leading PLSR algorithm because of its speed and efficiency. Because SIMPLS is based on the empirical cross-covariance matrix between the response variab...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Hereditas

سال: 2004

ISSN: 0018-0661

DOI: 10.1111/j.1601-5223.2004.01816.x