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Change point problems: Problems with chronologically ordered data collected over the period during which there is known to have been a change in the underlying data generation course. Interest then lies in, retrospectively, making the inferences about the time period or position in the sequence in which the change occurred. A well known example is the Lindisfarne scribes data in which a count is made of the occurrences of the certain type of pronoun ending observed in 13 chronologically order edmedievalmanu scripts thought to be the work of more than one author. A plot of data shows strong evidence of a change point in the below drawn figure. An easy example of the possible model for such a problem is as follows Interest would centre on estimating parameters in the model specifically the change point, τ
Geographical information system (gis): The software and hardware configurations through which the digital georeferences are processed and displayed. Used to recognize the geograph
Median is the value in a set of the ranked observations which divides the data into two parts of equal size. When there are an odd number of observations the median is middle v
The technique of sampling used in the ecology for determining how much plants or animals are in a given fixed region. A set of randomly placed lines or points is recognized and the
Longini Koopman model : In epidemiology the model for primary and secondary infection, based on the classification of the extra-binomial variation in an infection rate which might
Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre
The computer programs designed to mimic the role of the expert human consultant. This type of systems are capable to cope with the complex problems of the medical decision makin
Gllamm is a program which estimates the generalized linear latent and mixed models by the maximum likelihood. The models which can be fitted include structural equation models mul
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if nR2 > MTB >
Designs which permits two or more questions to be addressed in the investigation. The easiest factorial design is one in which each of the two treatments or interventions are p
Looking for the correct answer.Y=50+.079(149)-.261(214)=
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