পদ্ধতির তুলনা করুন

	পয়সোঁ ও নেগেটিভ বাইনোমিয়াল রিগ্রেশন	থিটা পদ্ধতি
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1998	2000
প্রবর্তক	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)	Assimakopoulos & Nikolopoulos
ধরন	Generalized linear model for count data	Univariate time-series forecasting model
মৌলিক উৎস	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.	Assimakopoulos, V. & Nikolopoulos, K. (2000). The Theta Model: A Decomposition Approach to Forecasting. International Journal of Forecasting, 16(4), 521-530.
অপর নাম	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon	theta model, theta forecasting, Theta Yöntemi — M3 Tahmin Yarışması Birincisi
সম্পর্কিত	4	4
সারসংক্ষেপ	Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred.	The Theta Method is a univariate time-series forecasting model introduced by Assimakopoulos and Nikolopoulos in 2000. It decomposes a series into two theta lines that capture its long-run trend and its short-run dynamics, forecasts each line separately, and combines them by a weighted average. Its simplicity and accuracy made it the winner of the M3 forecasting competition.