Regresyon analizlerinde bağımlı değişkenler normal dağılım gösterebilmekle birlikte iki değere sahip olabilirler. Bağımlı değişkenlere ilişkin durumlar nicel veya nitel olarak ölçümlenmesiyle veri setleri oluşturulur. Söz konusu gruplar içerisinde yer alan verilerin değerlendirilmesi ve modellenmesi için çeşitli yöntemler bulunmaktadır. Bu yöntemlerden birisi ise poisson regresyon modelidir. Ar...

Poisson log-linear models are ubiquitous in many applications, and one of the most popular approaches for parametric count regression. In Bayesian context, however, there no sufficient specific computational tools efficient sampling from posterior distribution parameters, standard algorithms, such as random walk Metropolis-Hastings or Hamiltonian Monte Carlo typically used. Herein, we developed...

A new area of research involves the use of normalized and scaled Google search volume data to predict economic activity. This new source of data holds both many advantages as well as disadvantages. Daily and weekly data are employed to show the effect of aggregation in Google data, which can lead to contradictory findings. In this paper, Poisson regressions are used to explore the relationship ...

BACKGROUND Traumatic placement of a needle during a neuraxial blockade has been related to many complications such as postdural puncture headache, trauma to neural structures and even spinal hematoma, causing permanent neurologic deficits. Although efforts to minimize the complications caused by traumatic neuraxial blockade have been made, nothing was found to be clear. The authors investigated...

For modeling count data, the Poisson regression model is widely used in which response variable takes non-negative integer values. However, presence of strong correlation between explanatory variables causes problem multicollinearity. Due to multicollinearity, variance maximum likelihood estimator (MLE) will be inflated causing parameters estimation become unstable. Multicollinearity can tackle...