Sentence examples for matrix of conditional from inspiring English sources

We show that for any mechanism there exists an equivalent dominant strategy incentive compatible mechanism for social choice environments with correlated types when agent's matrix of conditional probabilities satisfies the full rank condition.

A HMM model can thus be depicted by Λ=(A,B,π), in which the element of B (the matrix of conditional observation probability) is b i,k =Pr(O k |S i ), 1≤i≤8 and 1≤k≤16.

The matrix of conditional probabilities P is depicted as an image, with each pixel's color indicating the value of that matrix entry (on a logarithmic scale).

Apart from the mathematics, the major challenge in building a probabilistic model covering all causes of death to a reasonable level of detail lies in populating the matrix of conditional probabilities P(Ij∣Ci).

In the future, CDMS will allow the user to upload a sparse matrix of conditional probabilities so the calculation of EESN and EESP can be readily modified dynamically using empirically derived conditional probabilities during the tree search as needed.

In finance, multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models are by now a well-established method for calculating the covariance matrix of a conditional model.

In the second plot of Fig. 5 we show the matrix

The variance of an individual logistic regression equation is where V βi) and cov βi, βj) are from the estimated variance-covariance matrix of the conditional logistic regression estimates.

In Appendix A, the mean vector and variance-covariance matrix of the conditional distribution [ g| m obs ] (with M miss marginalised out) are shown to be Where (4) When all animals have been genotyped, G*(m obs ) = G(m obs ), and when no animals have been genotyped, G*(m obs ) = A, which makes the extension in (4) rather elegant.

where: ( {xi}_t=left{{varepsilon}_{it}/sqrt{h_{it}}right} ) is the vector englobing the standardized residuals derived from the univariate GARCH model estimation, as a matrix of these standardized residuals' conditional variance-covariance, whereas Q t  = {q ij,t } represents the unconditional variance-covariance matrix, which are temporally invariant.

where D i k = Λ i k H Λ i k and Ξ ̃ is the N T × N T unconditional covariance of transmitted chips, and is computed as the time average of conditional covariance matrices Ξ i ≜ diag σ 1, i 2, …, σ N T, i 2, where σ t, i 2 is the conditional variance of x t, i.