scholarly journals Ignoring uncertainty in predictor variables leads to false confidence in results: a case study of duck habitat use

Ecosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
Author(s):  
Adam C. Behney
Keyword(s):  
Habitat Use ◽  
Predictor Variables

Can animal habitat use patterns influence their vulnerability to extreme climate events? An estuarine sportfish case study

2017 ◽  
Vol 23 (10) ◽  
pp. 4045-4057 ◽  
Author(s):  
Ross E. Boucek ◽  
Michael R. Heithaus ◽  
Rolando Santos ◽  
Philip Stevens ◽  
Jennifer S. Rehage
Keyword(s):  
Habitat Use ◽  
Extreme Climate Events ◽  
Use Patterns ◽  
Extreme Climate ◽  
Climate Events ◽  
Animal Habitat

Snowmobile Effects on Movements of White-tailed Deer: A Case-study

1979 ◽  
Vol 6 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Ronald G. Eckstein ◽  
Thomas F. O'Brien ◽  
Orrin J. Rongstad ◽  
John G. Bollinger
Keyword(s):  
Home Range ◽  
Habitat Use ◽  
Odocoileus Virginianus ◽  
Activity Patterns ◽  
Home Range Size ◽  
Range Size ◽  
Home Ranges

The effects of snowmobile traffic on the winter home-ranges, movements, and activity patterns, of White-tailed Deer (Odocoileus virginianus), were studied during two winters in northern Wisconsin. There were no significant differences in home-range size and habitat use of the Deer in areas with and without snowmobiling. However, snowmobiling caused some Deer to leave the immediate vicinity of the snowmobile trail. Deer were most affected when they were within 61 m of the snowmobile trail.

scholarly journals PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017)

2019 ◽  
Vol 8 (1) ◽  
pp. 24-34
Author(s):  
Eka Destiyani ◽  
Rita Rahmawati ◽  
Suparti Suparti
Keyword(s):  
Least Squares ◽  
Robust Regression ◽  
Ordinary Least Squares ◽  
Regression Method ◽  
Predictor Variables ◽  
Healthy Life ◽  
Significance Level ◽  
Central Java ◽  
Regression Parameters

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM  Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords:  Ordinary  Least  Squares  (OLS),  Multicollinearity,  Outliers,  RidgeRegression, Robust Regression, AKB.

scholarly journals Spatial Distribution and Habitat Use of Javan Langur (Presbytis Comata): Case Study in District of Kuningan

2016 ◽  
Vol 33 ◽  
pp. 340-353 ◽  
Author(s):  
Toto Supartono ◽  
Lilik Budi Prasetyo ◽  
Agus Hikmat ◽  
Agus Priyono Kartono
Keyword(s):  
Spatial Distribution ◽  
Habitat Use
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