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1

Abdolell, Mohamed. Poisson regression trees. National Library of Canada, 1995.

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2

Abdolell, Mohamed. Poisson regression trees. Universiy of Toronto, Dept. of Statistics, 1994.

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3

Li, Joseph T. C. A poisson regression analysis of the academic setback in Naval Training deadtime. Naval Postgraduate School, 2000.

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4

Shi, Feng. Learn About Poisson Regression in R With Data From the Global Health Observatory (2015). SAGE Publications Ltd., 2019. http://dx.doi.org/10.4135/9781526473486.

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5

Gaver, Donald Paul. Regression analysis of hierarchical Poisson-like event rate data: Superpopulation model effect on predictions. Naval Postgraduate School, 1990.

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6

Lasse, Fridstrøm, and Nordic Council of Ministers, eds. Explaining the variation in road accident counts: A four-country, generalized Poisson regression analysis. Nordic Council of Ministers, 1993.

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7

Reid, Abigail-Kate, and Nick Allum. Learn About Poisson Regression in Stata With Data From the Behavioral Risk Factor Surveillance System (2013). SAGE Publications, Ltd., 2020. http://dx.doi.org/10.4135/9781529711387.

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8

Violent Crime and Poisson Regression. GRIN Verlag GmbH, 2013.

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9

Negative Binomial Regression. Cambridfe University Press, 2007.

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10

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2008.

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11

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2007.

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12

Negative Binomial Regression. Cambridge University Press, 2007.

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13

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2011.

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14

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2011.

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15

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2011.

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16

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2012.

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17

Hilbe, Joseph M. Negative Binomial Regression. Cambridge University Press, 2012.

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18

Negative binomial regression. 2nd ed. Cambridge University Press, 2011.

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19

Derek, A. GENERALIZED LINEAR MODELS. POISSON REGRESSION, LOGISTIC REGRESSION, DECISION TREES and DISCRIMINANT ANALYSIS. Lulu Press, Inc., 2020.

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20

Greene, William. Functional Form and Heterogeneity in Models for Count Data. Now Publishers Inc, 2007.

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21

Poisson Regression and the Behavioral Risk Factor Surveillance System (2013): Number of Servings of Fruit Consumed Daily. SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473961982.

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22

NANDE-VÁZQUEZ, Edgard Alfredo, Teodoro REYES-FONG, and Omar Alejandro PÉREZ-CRUZ. The Generalized Least Squares Method (GMM) as a tool for causal analysis of spending, budget management and electoral results. ECORFAN, 2021. http://dx.doi.org/10.35429/b.2021.8.1.130.

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Abstract:
In the different fields of science, many times, there is a need to estimate the associations between variables, as an approach to understanding the interaction of one as a function of the others. It is usually done by applying restrictive models, such as analysis of variance and linear regression. This type of analysis requires that the dependent variable be continuous, have a normal and constant distribution of the mean and variance. However, when the dependent variable is discrete or categorical, the linear model is not viable. Faced with this impediment, the theory of linear models arises a
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