Detection heterogeneity is inherent to ecological data, arising from factors such as varied terrain or weather conditions, inconsistent sampling effort, of individuals themselves. Incorporating additional covariates into a statistical model one approach for addressing heterogeneity, but no guarantee that any set measurable will adequately address the and presence unmodelled has been shown produ...

We propose parametric geons as a volumetric description of object components for qualitative object recognition. Parametric geons are seven qualitative shape types deened by parameterized equations which control the size and degree of tapering and bending. The models provide global shape constraints which make model recovery procedures robust against noise and minor variations in object shape. ...

Introduction: There is a lack of information on the extent of dependency between chronic diseases and the survival rate of breast cancer. Until date, none of the models proposed has determined the impact of chronic diseases on breast cancer survival. This study, therefore, aimed to investigate the impacts of chronic diseases such as diabetes, blood pressure, and endocrine di...

Introduction: There is a lack of information on the extent of dependency between chronic diseases and the survival rate of breast cancer. Until date, none of the models proposed has determined the impact of chronic diseases on breast cancer survival. This study, therefore, aimed to investigate the impacts of chronic diseases such as diabetes, blood pressure, and endocrine di...

Present study is about using of nonparametric models for GDP (Gross Domestic Product) per capita prediction in Turkey. It has been considered two alternative situations due to seasonal effects. In the first case, it is discussed a semi-parametric model where parametric component is dummy variable for the seasonality. In the second case, it is considered the seasonal component to be a smooth fun...

In the present research, data extracted from the stress analysis of 46 finite element models, verified using test results obtained from an experimental investigation, were used to study the effect of geometrical parameters on the chord-side stress concentration factors (SCFs) of central and outer braces in uniplanar tubular KT-joints of offshore structures subjected to four different types of i...

Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering of vector inputs is straightforward, extensions to structured data or time-series data remain less explored. This paper proposes a clustering method for time-series data that couples non-parametric spectral clustering with para...

Semiparametric estimation methods are used for models which are partly parametric and partly nonparametric; typically the parametric part is an underlying regression function which is assumed to be linear in the observable explanatory variables, while the nonparametric component involves the distribution of the model's ‘error terms’. Semiparametric methods are particularly useful for limited de...