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matlab例程 sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a G
sbgcop: Semiparametric Bayesian Gaussian copula estimation
This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data.
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其他书籍 sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a G
sbgcop: Semiparametric Bayesian Gaussian copula estimation
This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data.
...
数学计算 Markov分析的matlab工具包
Markov分析的matlab工具包，包含Markov回归分析等内容
matlab例程 Creates a Gaussian mixture model with specified architecture.MIX = GMM(DIM, NCENTRES, COVARTYPE) tak
Creates a Gaussian mixture model with specified architecture.MIX = GMM(DIM, NCENTRES, COVARTYPE) takes the dimension of the space
DIM, the number of centres in the mixture model and the type of the
mixture model, and returns a data structure MIX.
邮电通讯系统 Generate the digital AWGN signal n[k] (sampled n(t)) by generating zero mean Gaussian random variab
Generate the digital AWGN signal n[k] (sampled n(t)) by generating zero mean
Gaussian random variables independently (separately) for each k MATLAB function random.
3G开发 The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Proces
The MDP toolbox proposes functions related to the resolution of discrete-time Markov Decision Process : finite horizon, value iteration, policy iteration, linear programming algorithms with some variants.
The functions (m-functions) were developped with MATLAB v6.0 (one of the functions requires th ...
matlab例程 ％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input da
％ EM algorithm for k multidimensional Gaussian mixture estimation
％
％ Inputs:
％ X(n,d) - input data, n=number of observations, d=dimension of variable
％ k - maximum number of Gaussian components allowed
％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
％ ...
3G开发 This m file models a UWB system using BPSK with the fifth order derivative of the gaussian pulse wit
This m file models a UWB system using BPSK with the fifth order derivative of the gaussian pulse with correlation receiver and intgrator.
行业发展研究 Multiple alignment using hidden Markov models
Multiple alignment using hidden Markov models
人工智能/神经网络 General Hidden Markov Model Library 一个通用的隐马尔科夫模型的C代码库
General Hidden Markov Model Library 一个通用的隐马尔科夫模型的C代码库