scholarly journals Selection of tuning parameters in bridge regression models via Bayesian information criterion

2013 ◽  
Vol 55 (4) ◽  
pp. 1207-1223 ◽  
Author(s):  
Shuichi Kawano
Keyword(s):  
Bayesian Information Criterion ◽  
Regression Models ◽  
Information Criterion ◽  
Tuning Parameters ◽  
Selection Of

Optimizing age at first use of semen for higher fertilityin Sahiwal breeding bulls

2016 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat
Keyword(s):  
Comparative Evaluation ◽  
Regression Models ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
Progeny Testing ◽  
Testing Programme ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

The objective of the study was to optimise the age at first use (AAFU) of semen in Sahiwal breeding bulls which will help in early selection of bulls under progeny testing programme. The data on AAFU, conception rate based on first A.I. (CRFAI), overall conception rate (OCR) and birth weight (B.WT) of 43 Sahiwal bulls during 1987 to 2013 at NDRI centre pertaining to 8 sets of Sahiwal improvement programme at ICAR-NDRI, Karnal, India were adjusted for significant environmental influences and subsequently analyzed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Comparative evaluation of three developed models (I to III) have showed that Model III, having AAFU and B.WT which fulfill the accuracy of model as revealed by high coefficient of determination, low mean sum of square to due error, low conceptual predictive value and low Bayesian information criterion . The results showed that average predicted CRFAI was highest (49.34%) at less than 5 years and lowest (44.79%) at > 6 years of age at first A.I. /use. Similarly average predicted OCR was highest (48.50%) at less than 5 years and lowest (44.56%) at >6 years of age at first A.I. / use of Sahiwal bulls. In organized herd under progeny testing programme, Sahiwal bulls should be used prior to 5 years which is expected to result in 4.45% better CRFAI and 3.94% better OCR in comparison to Sahiwal bulls used after 6 years of age.

scholarly journals A Study of Count Regression Models for Mortality Rate

CAUCHY ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 142-151
Author(s):  
Anwar Fitrianto
Keyword(s):  
Mortality Rate ◽  
Regression Model ◽  
Count Data ◽  
Bayesian Information Criterion ◽  
Regression Models ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Information Criterion ◽  
Poisson Regression Model ◽  
Binomial Regression

This paper discusses how overdispersed count data to be fit. Poisson regression model, Negative Binomial 1 regression model (NEGBIN 1) and Negative Binomial regression 2 (NEGBIN 2) model were proposed to fit mortality rate data. The method used is comparing the values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to find out which method suits the data the most. The results show that the data indeed display higher variability. Among the three models, the model preferred is NEGBIN 1 model.

scholarly journals Drying kinetics of jabuticaba pulp by regression models

2019 ◽  
Vol 41 (1) ◽  
Author(s):  
Thais Destefani Ribeiro Furtado ◽  
Joel Augusto Muniz ◽  
Edilson Marcelino Silva ◽  
Jaqueline Gonçalves Fernandes
Keyword(s):  
Regression Models ◽  
Information Criterion ◽  
Drying Kinetics ◽  
Moisture Loss ◽  
Model Parameters ◽  
Drying Rate ◽  
Southern Brazil ◽  
Drying Time ◽  
Kinetics Of ◽  
Selection Of

Abstract Jabuticaba tree is native to the Atlantic Forest in Southern Brazil, and its fruit is widely consumed in the fresh form, but it is highly perishable, requiring conservation techniques. The aim of this study was to describe the drying kinetics of jabuticaba pulp at temperatures of 50 and 60°C, comparing the Henderson, Simple Three-Parameter Exponential, Lewis, Thompson, Fick and Wang and Sing regression models and estimating the Absolute Drying Rate (ADR) for the best model. Parameters were estimated using the SAS software. The evaluation of the quality in the adjustment and selection of models was made based on the adjusted determination coefficient, Residual Standard Deviation and Akaike Information Criterion. Models presented good adjustment to data, and the Lewis model was the most suitable to describe the drying kinetics of jabuticaba pulp at temperatures of 50 and 60°C, with drying rate of 0.000063 and 0.000082 g of water/s respectively. ADR indicated that in one third of the drying time, 70% of moisture loss occurred at both temperatures and after this period, there was a deceleration of moisture loss until stabilization, when equilibrium moisture content is reached.

Optimum age at first semen freezing in relation to fertility of Sahiwal breeding bulls

2018 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat ◽  
Ramendra Das ◽  
...  
Keyword(s):  
Birth Weight ◽  
Regression Models ◽  
Dairy Herd ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
National Dairy Research Institute ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

Early selection of bulls having optimum age at first semen freezing play an important role in improving reproductive performance in a dairy herd. Twenty seven years data (1987-2013) on age at first semen freezing (AAFSF), conception rate based on first A.I. (CRFAI) , overall conception rate (OCR) and birth weight (B.WT) of 41 Sahiwal bulls belonging to 8 sets of Sahiwal improvement programme at ICAR-National Dairy Research Institute, Karnal, Haryana, India; were adjusted against environmental effects and subsequently analysed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Among the three developed models (I to III), it was observed that Model III having age at first semen freezing and birth weight fulfil the accuracy of model i.e.; having high coefficient of determination (R2) value (CRFAI = 67% and OCR= 69%), low mean error sum of square (MSSe), low conceptual predictive value (CP value) and low Bayesian information criterion (BIC). The results revealed that optimum age at first semen freezing of Sahiwal bulls should be 2.5 - 3.0 years for 3.10% higher conception rate based on first A.I. (48.86%) and 4.39% higher overall conception rate (48.78%) in comparison to Sahiwal bulls with more than 3.5 years of age (CRFAI :- 45.76% and OCR :- 44.39%).

scholarly journals Modelling Claim Frequency in Insurance Using Count Models

2021 ◽  
pp. 14-20
Author(s):  
A. Adetunji Ademola ◽  
Shamsul Rijal Muhammad Sabri
Keyword(s):  
Bayesian Information Criterion ◽  
Regression Models ◽  
Negative Binomial ◽  
Predictive Ability ◽  
Information Criterion ◽  
Information Criteria ◽  
Binomial Model ◽  
Count Models ◽  
Claim Frequency ◽  
Insurance Data

Background: In modelling claim frequency in actuary science, a major challenge is the number of zero claims associated with datasets. Aim: This study compares six count regression models on motorcycle insurance data. Methodology: The Akaike Information Criteria (AIC) and the Bayesian Information Criterion (BIC) were used for selecting best models. Results: Result of analysis showed that the Zero-Inflated Poisson (ZIP) with no regressors for the zero component gives the best predictive ability for the data with the least BIC while the classical Negative Binomial model gives the best result for explanatory purpose with the least AIC.

Sign in / Sign up

Export Citation Format

Share Document