Rainfall is one of the climatic elements in tropics which very influential agriculture, especially determining growing season. Thus, proper rainfall modeling needed to help determine best time start cultivating soil. can be done using Statistical Downscaling (SDS) method. SDS a statistical model field climatology analyze relationship between large-scale and small-scale climate data. This study ...

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partia...

Variable selection has been a hot topic, with various popular methods including lasso, SCAD, and elastic net. These penalized regression algorithms remain sensitive to noisy data. Furthermore, “concept drift” fundamentally distinguishes streaming data learning from batch learning. This article presents method for noise-resistant regularization variable in streams multicollinearity, dubbed canal...

This study aims to see the influence of investment decisions measured by Price Earning Ratio (PER) and dividend policy Dividend Payout (DPR) on company value Book Value (PBV). The sample this consisted 11 companies included in LQ-45 group listed Indonesia Stock Exchange (IDX). uses classical assumption tests (nomality test, multicollinearity heteroscedasticity autocorrelation test) hypothesis w...

When developing prediction models for small or sparse binary data with many highly correlated covariates, logistic regression often encounters separation multicollinearity problems, resulting serious bias and even the nonexistence of standard maximum likelihood estimates. The combination makes task more difficult, a few studies addressed simultaneously. In this paper, we propose double-penalize...

This study aims to determine the effect of Corporate Social Responsibility (CSR) and Financial Distress on Tax Aggressiveness during 2018 – 2022 period, which obtained 30 data in this study. The type used is secondary data, form company's annual report. Data analysis descriptive statistics, classical assumption test, coefficient determination multiple linear regression analysis. processing uses...

Multicollinearity is considered to be a significant problem in the estimation of parameters not only general linear models, but also generalized models (GLMs). Thus, order alleviate serious effects multicollinearity new estimator proposed by combining ridge and PCR estimators GLMs. This called r-k class The various comparisons are made with already existing literature, which maximum likelihood ...