예제 및 방법
- Set Up Multivariate Regression Problems
To fit a multivariate linear regression model using
mvregress, you must set up your response matrix and design matrices in a particular way.
- Multivariate General Linear Model
This example shows how to set up a multivariate general linear model for estimation using
- Fixed Effects Panel Model with Concurrent Correlation
This example shows how to perform panel data analysis using
- Longitudinal Analysis
This example shows how to perform longitudinal analysis using
- 부분 최소제곱 회귀 및 주성분 회귀
부분 최소제곱 회귀(PLSR) 및 주성분 회귀(PCR)를 적용하고 이 두 방법의 효과를 살펴봅니다.
- Multivariate Linear Regression
Large, high-dimensional data sets are common in the modern era of computer-based instrumentation and electronic data storage.
- Estimation of Multivariate Regression Models
When you fit multivariate linear regression models using
mvregress, you can use the optional name-value pair
'algorithm','cwls'to choose least squares estimation.
- Partial Least Squares
Partial least squares (PLS) constructs new predictor variables as linear combinations of the original predictor variables, while considering the observed response values, leading to a parsimonious model with reliable predictive power.