Log-Transform Kernel Density Estimation of Income Distribution
نویسندگان
چکیده
منابع مشابه
Improved Fast Gauss Transform and Efficient Kernel Density Estimation
Evaluating sums of multivariate Gaussians is a common computational task in computer vision and pattern recognition, including in the general and powerful kernel density estimation technique. The quadratic computational complexity of the summation is a significant barrier to the scalability of this algorithm to practical applications. The fast Gauss transform (FGT) has successfully accelerated ...
متن کاملKernel Density Estimation
Preface The following diploma thesis is thought to be a diploma thesis in applied statistics. I declare this in the first paragraph of my work, because you can treat this subject either from a theoretic or an applied view, although the borders between these two areas of statistics cannot be drawn exactly. The reason why I got the idea to treat this subject, is that on the one hand density estim...
متن کاملFiltered Kernel Density Estimation
A modification of the kernel estimator for density estimation is proposed which allows the incorporation of local information about the smoothness of the density. The estimator uses a small set of bandwidths rather than a single global one as in the standard kernel estimator. It uses a set of filtering functions which determine the extent of influence of the individual bandwidths. Various versi...
متن کاملContingent Kernel Density Estimation
Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is no...
متن کاملAdaptive kernel density estimation
This insert describes the module akdensity. akdensity extends the official kdensity that estimates density functions by the kernel method. The extensions are of two types: akdensity allows the use of an “adaptive kernel” approach with varying, rather than fixed, bandwidths; and akdensity estimates pointwise variability bands around the estimated density functions.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: L'Actualité économique
سال: 2016
ISSN: 1710-3991,0001-771X
DOI: 10.7202/1036917ar