MITE
发表于 2025-3-26 23:05:37
http://reply.papertrans.cn/24/2336/233600/233600_31.png
maculated
发表于 2025-3-27 05:08:27
http://reply.papertrans.cn/24/2336/233600/233600_32.png
Density
发表于 2025-3-27 08:51:15
http://reply.papertrans.cn/24/2336/233600/233600_33.png
MIR
发表于 2025-3-27 09:56:14
http://reply.papertrans.cn/24/2336/233600/233600_34.png
泛滥
发表于 2025-3-27 15:15:03
http://reply.papertrans.cn/24/2336/233600/233600_35.png
文艺
发表于 2025-3-27 20:17:21
Intensive Numerical and Symbolic Computing in Parametric Test Theoryl regions with particular optimality properties, . computing to obtain a better understanding of a statistical model e.g. by giving the geometry of the model. Each level is explained in the construction of two tests for a simple null hypothesis in two lifetime models..The .-LMMPUM. test maximizes th
序曲
发表于 2025-3-28 01:41:00
Learning Data Analysis and Mathematical Statistics with a Macintoshtics and the practice of data analysis. The authors developed a set of lectures notes with a strong emphasis on: Graphical analyses, random number generation, simulation techniques, resampling methods, dynamic illustration of regression diagnostics, robust methods ... . Most of these concepts can be
大包裹
发表于 2025-3-28 03:30:15
Markov Random Field Models in Image Remote Sensingontext of conditional maximum likelihood estimation. Here, in the same context, we propose some original uses of Mrf, especially in image segmentation, noise filtering and discriminant analysis. For instance, we propose a Mrf model on the spectral signatures space, a strongly unified approach to cla
带来
发表于 2025-3-28 06:42:42
Bandwidth Selection for Kernel Regression: a Surveye. the bandwidth). Bandwidth choice turns out to be of particular importance as well for practical use as to insure good asymptotic properties of the estimate. Various techniques have been proposed in the past ten last years to select optimal values of this parameter. This paper presents a survey on
beta-carotene
发表于 2025-3-28 13:55:53
Application of Resampling Methods to the Choice of Dimension in Principal Component Analysissessing the stability of the fit is considered. The choice of dimension then amounts to the minimisation of an expected loss which has to be estimated. This is achieved by resampling methods. Different bootstrap and jackknife estimates are presented. The behaviour of these estimates are investigated