By observing the diffusion process X(t) which satisfies the following equation: dX(t)=b(X(t),θ)dt+dW(t),X(0)=x_0,t≥0,the maximum likelihood estimator _t about the parameter θ in the drift coefficient (b(X(t),θ)) is given.
The maximum likelihood estimation value of DN800,DN700,DN600 are 0.31,0.28 and 0.24 in turn,and the confidence interval are respectively 0.24～0.38,0.23～0.33 and 0.22～0.26.The data can be used for engineering design in central heating.
Three methods:Modified Covariance Method (MCOV),Recursive Maximum Likelihood Estimator (RMLE) and Burg Method are used to solve AR parameters and compared the influence to recovered spectrum from AR order,signal-to-noise ratio.
采用三种方法:修正协方差法MCOV(Modified Covariance Method)、递推极大似然估计法RMLE(Recursive Maximum Likelihood Estimator)和伯格法(Burg Method)求解线型优化最大熵线性预测方法中的自回归模型系数,并且在不同求解方法情况下,将阶次、信噪比对光谱复原的影响作了详尽的比较.
For 2 p-multiple normal populations with unknown mean vector θ i and unknown covariance matrix ∧ i, i=1, 2, assume that there are some order restrictions among the mean vectors and covariance matrices respectively, for example, simple order restrictions: θ 1≤θ 2 and ∧ 1≥∧ 2>0. Some properties of maximum likelihood estimations of θ is and ∧ is are discussed and some results are obtained.
This paper considers the estimating and testing problem of odds ratios for k 2×2 cross-classification tables under ψ 1≤ψ 2≤…≤ψ k , and give an algorithm to obtain the MLE. It also proves that the maximum likelihood ratio test under ψ 1=ψ 2=…=ψ k is χ -2 .
The study shows that the overall accuracy of maximum likelihood is about 84.89%, and Kappa Coefficient = 0.74, while overall accuracy of binary encoding , neural net and spectral angle mapping is 87.12%,88.75%,90.41% respectively.
Result Segregation ratios were 25.372±0.127% for U×U mating type and 23.839±0.732% for U×A mating type thr ough maximum likelihood estimation method. Segregation ratios were 25.1 3% for U×U mating type and 37.37% for U×A mating type through theoretical children methods.
The relative efficiencies of moment estimators as compared with the maximum likelihood and the stepwise estimators are computed.
Generalized Maximum Likelihood Algorithm for Direction-of-Arrival Estimation of Coherent Sources
The generalized maximum likelihood (GML) algorithm for direction-of-arrival estimation is proposed.
Secondly, the comparison between the GML algorithm and the conventional deterministic maximum likelihood (DML) algorithm is presented based on their respective geometrical interpretation.
In this article, we developed a new algorithm for eigenspace-based adaptation restricting eigenvoices in clustered subspaces, and maximum likelihood (ML) criterion was replaced with maximum aposteriori (MAP) criterion for better parameter estimation.