In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
標簽： sequential simulation posterior overview
上傳時間： 2015-12-31
上傳用戶：225588
很全的中斷手冊。 INT 00 - CPU-generated - DIVIDE ERROR INT 01 - CPU-generated - SINGLE STEP (80386+) - DEBUGGING EXCEPTIONS INT 02 - external hardware - NON-MASKABLE INTERRUPT INT 03 - CPU-generated - BREAKPOINT INT 04 - CPU-generated - INTO DETECTED OVERFLOW INT 05 - PRINT SCREEN CPU-generated (80186+) - BOUND RANGE EXCEEDED INT 06 - CPU-generated (80286+) - INVALID OPCODE INT 07 - CPU-generated (80286+) - PROCESSOR EXTENSION NOT AVAILABLE INT 08 - IRQ0 - SYSTEM TIMER CPU-generated (80286+) . . .
標簽： CPU-generated INT DIVIDE SINGLE
上傳時間： 2013-12-27
上傳用戶：aa54
Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.
標簽： meta-learning classifiers combining Boosting
上傳時間： 2016-01-30
上傳用戶：songnanhua
《SPSS 11統計分析教程》（高級篇）樣章，第一章：征服一般線性模型――General Linear Model菜單詳解（上）第一節：方差分析模型簡介，PDF格式。
上傳時間： 2016-02-04
上傳用戶：semi1981
數據庫系統實現，linear hash算法
標簽： 數據庫系統
上傳時間： 2016-02-05
上傳用戶：aa17807091
Traveling Salesman Problem (TSP) has been an interesting problem for a long time in classical optimization techniques which are based on linear and nonlinear programming. TSP can be described as follows: Given a number of cities to visit and their distances from all other cities know, an optimal travel route has to be found so that each city is visited one and only once with the least possible distance traveled. This is a simple problem with handful of cities but becomes complicated as the number increases.
標簽： interesting Traveling classical Salesman
上傳時間： 2016-02-06
上傳用戶：rocwangdp
PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis practice. For the latter part it is assumed (but not absolutely necessary) that the reader is already familiar with these methods. It also assumes you have had some preliminary experience with linear/matrix algebra.
標簽： Component Principal Analysis bilinear
上傳時間： 2016-02-07
上傳用戶：zuozuo1215
Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique.
標簽： performance equalizers Adaptive several
上傳時間： 2016-02-16
上傳用戶：yan2267246
This program is copyrighted by it s author and you are granted a free license to use the program for non-commercial purposes. If you are interested in using the program for commercial purposes please contact Kevin W. Russell at CIS 71551,253 for licensing information.
標簽： program copyrighted granted license
上傳時間： 2016-02-18
上傳用戶：wangzhen1990
On Sunday, April 27, 2003, Fresno will celebrate Earth Day in downtown Fresno at Courthouse Park. The event will begin at noon. This year we will include music, speakers, and vendors, plus activities for children. Fresno Earth Day is recognized as the only Earth Day festival that happens in Fresno, and the largest in the Central Valley. The Fresno Earth Day Committee is a small group of environmental activists hoping to broaden the appeal of a better planet and environment. We are a non-profit organization whose fiscal fiduciary is the Fresno Center for Nonviolence.
標簽： Fresno Courthouse celebrate downtown
上傳時間： 2016-02-24
上傳用戶：cursor
