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Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probability 1 p a random variable with the Poisson distribution is observed. For instance, when manufacturing equipment is properly aligned, defects might be almost impossible. But when it is misaligned, defects might happen according to a Poisson distribution. Both probability p of the perfect zero defect state and the mean number of defects λ in the imperfect state might depend on covariates. The parameters in this type of models can be estimated using maximum likelihood estimation.
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
Catastrophe theory : A theory of how little is the continuous changes in the independent variables which can have unexpected, discontinuous effects on the dependent variables. Exam
Mean squarederror is the expected value of square of the difference between an estimator and the true value of the parameter. If the estimator is unbiased then the mean of the squ
a shop is selling laptops at regular price and at half price.If the laptops are regular price a day they will be at regular price tha day after with proba 2/3, if the laptops are a
Oracle property is a name given to techniques for estimating the regression parameters in the models fitted to high-dimensional data which have the property that they can correctl
difference between histogram and historigram
The probability distribution of the various observations is required to obtain the run of two successes in the series of Bernoulli trials with the probability of success equal to a
Multidimensional scaling (MDS) is a generic term for a class of techniques or methods which attempt to construct a low-dimensional geometrical representation of the proximity matr
Non-identified response is a term used to signify censored observations in survival data, which are not independent of the endpoint of the interest. Such observations can happen f
1) Has smartphones affected the consumer behavior? If so How ? And how is it going to change in future? 2) Forecasting of Mobile market (Time series analysis) 3) Comparison of fou
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