Search - maximum likelihood estimation

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[matlab] Maximum likelihood estimation of GARCH DL : 0: Maximum likelihood estimation of GARCH
Date : 2012-07-18 Size : 1.14kb User : stanleyjunjun
[Program doc] carieroffset-estimation DL : 0: Tdscdma系统中的载频估计程序，利用导频段，极大似然的估计算法，在MATLAB中的实现程序-Tdscdma system of carrier frequency estimation procedures, the use of derivative band, the maximum likelihood estimation algorithm, MATLAB in the realization process
Date : 2025-07-04 Size : 2kb User : 青青
[Other] gamma_fit DL : 1: 这是一个基于matlab且运用极大似然估计法对伽马分布进行拟合-This is a matlab-based and the use of maximum likelihood estimation method for gamma distribution fitting
Date : 2025-07-04 Size : 1kb User : 杨芮
[matlab] FitFunc DL : 0: 本算法包括最大似然估计，最小二乘估计，基于EM算法的多种混合高斯分布估计，EM算法测试实例，绘制每种分布的plot函数。非常有参考价值！-This algorithm, including maximum likelihood estimation, least squares estimation, based on the EM algorithm estimate a mixture Gaussian distribution, EM algorithm for the test examples, each mapping the distribution of the plot function. Very useful!
Date : 2025-07-04 Size : 22kb User : liyuedsg
[Books] MLE DL : 0: 3 books about distance function and Maximum Likelihood Estimation: Earth s Mover Distance, Kullback-Leibler, MLE
Date : 2025-07-04 Size : 1.81mb User : ChipChipKnight
[matlab] mle DL : 0: maximum likelihood estimation
Date : 2025-07-04 Size : 9kb User : houl
[matlab] Tutorial-on-maximum DL : 0: Tutorial on maximum likelihood estimation
Date : 2025-07-04 Size : 295kb User : qq
[matlab] OUProcess DL : 0: This program calibrates the Ornstein–Uhlenbeck process, a mean reverting AR(1) stochastic process. The parameters are estimated using (1)Least Squares fitting and (2)Maximum Likelihood estimation.-This program calibrates the Ornstein–Uhlenbeck process, a mean reverting AR(1) stochastic process. The parameters are estimated using (1)Least Squares fitting and (2)Maximum Likelihood estimation.
Date : 2025-07-04 Size : 1kb User : panda
[matlab] lognormal DL : 0: Maximum Likelihood estimation for lognormal pdf
Date : 2025-07-04 Size : 1kb User : Ercu1
[matlab] normal DL : 0: Maximum likelihood estimation for normal
Date : 2025-07-04 Size : 1kb User : Ercu1
[matlab] mix_gaussian DL : 0: Maximum likelihood estimation for mixed gaussian function
Date : 2025-07-04 Size : 1kb User : Ercu1
[matlab] homework_1_1 DL : 0: 最大似然估计法的matlab实现，及Crammer-lor下界的确定-Maximum likelihood estimation of the matlab implementation, and Crammer-lor to determine the lower bound
Date : 2025-07-04 Size : 1kb User : dago
[Algorithm] cml DL : 0: Constrained Maximum Likelihood Estimation
Date : 2025-07-04 Size : 58kb User : riag
[matlab] Maximum-likelihood-parameter-estimation DL : 0: this code is or estimation Maximum likelihood parameter
Date : 2025-07-04 Size : 1kb User : rezi
[matlab] matlab-mle DL : 0: 主要是介绍极大似然估计并用matlab实现极大似然估计-Is to introduce the maximum likelihood estimation and use matlab to achieve maximum likelihood estimation
Date : 2025-07-04 Size : 40kb User : he
[matlab] Maximum-Likelihood-Estimation DL : 0: Maximum Likelihood Estimation Step 1. : Estimate the mean vector and covariance of an arbitrary 3-class dataset with bi-variate Gaussian distribution by maximum likelihood estimation An arbitrary 3-class dataset is given (by Dataset.mat) and the priors are equal. Step 2. : If three arbitrary samples are given as follows, determine to which class each sample should belong. Let arbitrary samples are as follows: Z_1=[50 50]^T, Z_2=[10 20]^T, Z_3=[0 20]^T-Maximum Likelihood Estimation Step 1. : Estimate the mean vector and covariance of an arbitrary 3-class dataset with bi-variate Gaussian distribution by maximum likelihood estimation An arbitrary 3-class dataset is given (by Dataset.mat) and the priors are equal. Step 2. : If three arbitrary samples are given as follows, determine to which class each sample should belong. Let arbitrary samples are as follows: Z_1=[50 50]^T, Z_2=[10 20]^T, Z_3=[0 20]^T
Date : 2025-07-04 Size : 23kb User : jyju
[CSharp] Maximum-Likelihood-Estimation DL : 0: 用MATLAB编写代码,在经济和金融中法对连续时间过程实现了封闭的最大似然估计方法-The code, written in MATLAB, implements the closed-form maximum-likelihood estimation method for continuous-time processes in economics and finance. First, the code maximizes the log-likelihood function and displays the MLE estimates, the standard error estimates (constructed from the inverse of Hessian) and the misspecification-robust standard error (i.e., the sandwich estimate). Second, it reports whether the maximization procedure converges under the default tolerance. Finally, it plots the marginal log-likelihood for each parameter in a neighborhood of the estimates. The blue curve is the likelihood function, while each red star corresponds to the estimate for the corresponding parameter. For more information about the models, please read the user s guide (link "more").
Date : 2025-07-04 Size : 253kb User : 雪之恋
[Software Engineering] a-noive-maximum-likelihood-estimation-for-lin DL : 0: a noive maximum likelihood estimation for linear model by MLE
Date : 2025-07-04 Size : 2kb User : xujie
[Software Engineering] maximum-likelihood-estimation-method-can-be-used- DL : 0: maximum likelihood estimation method can be used to very broad estimation
Date : 2025-07-04 Size : 2kb User : xujie
[matlab] Maximum-likelihood-estimation DL : 0: 统计信号处理实验最大似然估计有完整的实验报告个、和源代码-Maximum likelihood estimation for statistical signal processing experiments Have complete experiment report, and source code
Date : 2025-07-04 Size : 133kb User : 毛荣钧

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