Emergence of DNA microarray datasets started up a crucial research subject for both bioinformatics and machine learning. This type of data is obtained from tissue or cell samples and used to collect information that may ...

Spatial analysis is a method used to describe spatial patterns on a geographical region. During this analysis, the attributes and location information of the objects forming the spatial data are used. Response variable ...

Weibull distributions are one of the most popular continuous distributions used in survival analysis for modeling error / failure times such as deterioration and wear, early death. Nowadays, this distribution is used to ...

In today’ s conditions, increasing the need for such as assessing, analyzing and making forward estimates of data, has increased the demand for data mining methods. In this study, classification and regression estimating ...

In today's economic conditions, states must cooperate with the private sector in economic situations where it is not possible for them to offer public services. At this point where states and private sector meet, the ...

The joint distribution of categorical variables is summarized by the contingency table. The R × R dimensional contingency tables in which the variables are cross classified according to the same criteria with the number ...

Since there are no theoretical constraints such as the model assumption and the number of observations, the importance of the preferred fuzzy time series instead of classical time series is day by day increasing in analysis ...

The use of regression models with fractional polynomial was proposed to model nonlinear effects of covariates. The inclusion of continuous covariates as continuous in the model and its inclusion in the model as a categorical ...

Determining the economic variables that affect credit default swap spreads which are known as indicator of country risk and modelling these spreadss have great importance in terms of financial world. In this study, after ...

This study deals with implementing three different types of dynamic linear models using dlm package in R. These models are the steady model, the linear growth model and the combined model as a second order polynomial model ...