Fitting the linear regression model and logistic model to livestock and poultry population
Date of Publication
1992
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Mathematics
College
College of Science
Department/Unit
Mathematics and Statistics
Abstract/Summary
This thesis is a comparative study of two kinds of forecasting models-the causal model and extrapolation model as applied to livestock and poultry population data. The causal model represented by the linear regression analysis is pitted against a time series extrapolation model represented by the logistic growth curve. Two separate regression models are computed using the data while the logistic growth curve for the different animal populations is estimated using two distinct estimation procedures resulting in two separate logistic models. These four models are then run in parallel to determine their forecasting efficiency.
Abstract Format
html
Language
English
Format
Accession Number
TU05855
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
82 leaves
Keywords
Curve fitting; Regression analysis; Livestock--Mathematical models; Linear programming; Poultry; Animal populations; Populations, Animal
Recommended Citation
Anes, I. M., & De Leon, J. P. (1992). Fitting the linear regression model and logistic model to livestock and poultry population. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/16019
