Results 71 to 80 of about 300,687 (184)

Machine learning of large‐scale spatial distributions of wild turkeys with high‐dimensional environmental data

Ecology and Evolution, 2019
Species distribution modeling often involves high‐dimensional environmental data. Large amounts of data and multicollinearity among covariates impose challenges to statistical models in variable selection for reliable inferences of the effects of ...
Annie Farrell, Guiming Wang, Scott A. Rush, James A. Martin, Jerrold L. Belant, Adam B. Butler, Dave Godwin   +6 more
doaj   +1 more source

On the Identification of Time Varying Structures [PDF]

The identifiability of reduced form econometric models with variable coefficients is investigated using the control theoretic concepts of uniform complete observability and uniform complete controllability.
Kent D. Wall, Thomas F. Cooley
core  

New robust ridge-type estimators for beta regression under multicollinearity and outliers with application to breast cancer data

Applied Mathematics in Science and Engineering
The beta regression model (BRM) is a widely applied modeling approach for data bounded within the open interval (0, 1), and it is extensively used in fields such as chemistry, environmental science, medicine, and biology.
Ali T. Hammad, I. Elbatal, Ohud A. Alqasem, Ehab M. Almetwally, Amin M. A. Haleeb, Abdirashid M. Yousuf, M. M. Abd El-Raouf, Ahmed M. Gemeay   +7 more
doaj   +1 more source

MULTICOLLINEARITY IN REGRESSION WITH QUADRATIC REGRESSORS [PDF]

Research Methods/ Statistical Methods,
Griffiths, William E.
core   +1 more source

Crime prediction through urban metrics and statistical learning

, 2018
Understanding the causes of crime is a longstanding issue in researcher's agenda. While it is a hard task to extract causality from data, several linear models have been proposed to predict crime through the existing correlations between crime and urban ...
Alves, Luiz G A, Ribeiro, Haroldo V, Rodrigues, Francisco A   +2 more
core   +1 more source

Robust Kibria Estimators for Mitigating Multicollinearity and Outliers in a Linear Regression Model

Stats
In the presence of multicollinearity, the ordinary least squares (OLS) estimators, aside from BLUE (best linear unbiased estimator), lose efficiency and fail to achieve minimum variance.
Hina Naz, Ismail Shah, Danish Wasim, Sajid Ali   +3 more
doaj   +1 more source

ON MODELING SYSTEMS OF CROP ACREAGE DEMANDS [PDF]

This article presents an alternative approach to the specification of systems of crop acreage responses. Derived demands for acreages of individual crops are specified as conditional on total crop acreage, and related separability and dynamic ...
Coyle, Barry T.
core   +1 more source

The Effect of Current Ratio, Debt to Equity Ratio, Toward Return on Assets (Case Study on Consumer Goods Company) [PDF]

, 2018
This study aims to detect the effect liquidity ratio, leverage ratio and profitability on consumer goods companies listing on the Indonesia Stock Exchange 2014 – 2017.
Hantono, H. (Hantono)
core  

Stochastic Restricted Biased Estimators in misspecified regression model with incomplete prior information

, 2018
In this article, the analysis of misspecification was extended to the recently introduced stochastic restricted biased estimators when multicollinearity exists among the explanatory variables.
Kayanan, Manickavasagar, Wijekoon, Pushpakanthie   +1 more
core   +2 more sources

Feasible robust Liu estimator to combat outliers and multicollinearity effects in restricted semiparametric regression mode

AIMS Mathematics
Regression analysis frequently encounters two issues: multicollinearity among the explanatory variables, and the existence of outliers in the data set.
W. B. Altukhaes, M. Roozbeh, N. A. Mohamed   +2 more
doaj   +1 more source