Modelling heterogeneity among fitness functions using random regression

Detecting “bad” regression models: multicriteria fitness functions in regression analysis

Regression models with good fitting but no predictive ability are sometimes chance correlations and often show some pathological features such as multicollinearity, overfitting, and inclusion of noisy/spurious variables. This problem is well known and of the utmost importance. The present paper proposes some criteria that are to be fulfilled as conditions for model acceptability, the aim being ...

Modelling using polynomial regression

This paper is concentrated on the polynomial regression model, which is useful when there is reason to believe that relationship between two variables is curvilinear. The polynomial regression model has been applied using the characterisation of the relationship between strains and drilling depth. Parameters of the model were estimated using a least square method. After fitting, the model was e...

Random regression models for estimation of covariance functions of growth in Iranian Kurdi sheep

Body weight (BW) records (n=11,659) of 4961 Kurdi sheep from 215 sires and 2085 dams were used to estimate the additive genetic, direct and maternal permanent environmental effects on growth from 1 to 300 days of age. The data were collected from 1993 to 2015 at a breeding station in North Khorasan province; Iran. Genetic parameters for growth traits were estimated using random regression test-...

Modelling Invasion Dynamics with Spatial Random-Fitness due to Microenvironment

Numerous experimental studies have demonstrated that the microenvironment is a key regulator influencing the proliferative and migrative potentials of species. Spatial and temporal disturbances lead to adverse and hazardous microenvironments for cellular systems that is reflected in the phenotypic heterogeneity within the system. In this paper, we study the effect of microenvironment on the inv...

Stochastic Modelling Probability Theory of Random Functions Random Variables Random Functions Spectral Representation of Random Functions Isotropic Incompressible Random Functions Transformations of Random Functions Derivation of Stochastic Models Quasi Homogeneous Random Functions Filtering of Random Functions