A fully automated smoothing procedure for uniformly-sampled datasets is described. The algorithm, based on a penalized least squares method, allows fast smoothing of data in one and higher dimensions by means of the discrete cosine transform. Automatic choice of the amount of smoothing is carried out by minimizing the generalized cross-validation score. An iteratively weighted robust version of...

To determine the effect of membership of the Royal College of General Practitioners (RCGP) on recognition of depression, odds ratios, Lowess-smoothed plots, and regression models were produced for recognition rates in a representative sample of 20,818 patient contacts for members and non-members of the RCGP Membership of the RCGP did not appear to convey greater ability to discriminate between ...

background:although intellectual disability (id) is a common disability in iran, there is no investigation on the spatial distribution pattern of these patients in national level and the spatial maps for recognition the areas with higher prevalence of ids and local neighborhoods of these regions or effect of socio-demographic factor on this scattering is not still available. this proposition mo...

It is known that the fitted regression function based on conventional local smoothing procedures is not statistically consistent at jump positions of the true regression function. In this article, a curve-fitting procedure based on local piecewise-linear kernel estimation is suggested. In a neighborhood of a given point, a piecewise-linear function with a possible jump at the given point is fit...

[To be revised.] Quantile and expectile regression are tail oriented conditional regression. They can be transformed as generalized quantile regression. Traditional generalized quantile regression focuses on a single curve. When more random curves are available, we can estimate the single curves jointly by using the information from all subjects instead of estimate it individually. To avoid too...

T here is always uncertainty about the soundness of an economic model’s structure and parameters. Therefore, central banks normally face with uncertainty about the key economic explanatory relationships. So, policymaker should take into account the uncertainty in formulating monetary policies. The present study is aimed to examine robust optimal monetary policy under uncertainty, by ...

In addition to the standard risk factors suggested by asset pricing models, extant literature shows mixed evidence of impact market structure on firm-level returns. Using data for 940 Indian firms listed Bombay Stock Exchange across 65 industries between FY 2010–11 FY2018-19 and Lowess smoothing followed a robust regression model with time fixed industry effects, we find that in more concentrat...

Geographically weighted regression (GWR) was introduced to the geography literature by Brunsdon et al. (1996) to study the potential for relationships in a regression model to vary in geographical space, or what is termed parametric nonstationarity. GWR is based on the non-parametric technique of locally weighted regression developed in statistics for curve-fitting and smoothing applications, w...

Kemiskinan masih menjadi masalah utama dalam pembangunan bagi setiap daerah, termasuk Daerah Istimewa Yogyakarta. sendiri terjadi salah satunya karena disebabkan oleh tingginya tingkat pengangguran, ketimpangan antara daerah perdesaan dan perkotaan ikut penyebab semakin kemiskinan di perdesaan. Industri mikro kecil merupakan sektor yang dapat tumbuh seluruh wilayah menyerap tenaga kerja jumlah ...