Fitting the linear regression model and logistic model to livestock and poultry population
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 lo...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
1992
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/16019 |
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| Institution: | De La Salle University |
| Language: | English |
| 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. |
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