Sentence examples for matrix of errors from inspiring English sources

The problem studied in the paper concerns the estimation of individual weights of p objects according to the model of an A-optimal chemical balance weighing design with a positive definite diagonal variance matrix of errors under the restriction p1+p2= q⩽p, where p1 and p2 represent the numbers of objects placed on the left and on the right pan, respectively, in each of the measurement operations.

The rows of the n × p matrix of errors, E, are assumed to be independent and identically distributed draws from a multivariate normal distribution.

The standard unadjusted EWAS analysis (on beta values) posits the linear model (1) where is an matrix of coefficients and is an matrix of errors.

P t,t−1) is the one-step prediction of the matrix of error covariance at moment t.

9 Due to the criterion of additivity, the variance‐covariance matrix of error terms for a complete equation demand system will be singular.

Secondly, with the matrix of error covariance and observability of the system, this paper designs a vector-form information sharing algorithm so that each state variable can get a different coefficient.

We use the average absolute value of differences between true and inferred frequencies as a matrix of error.

Here Y is the J × n matrix of observed blood glucose measurements; Φ is the J ×  K matrix of the values of the K basis functions evaluated at times t j, and the J ×  n matrix of error terms.

According to the spot forecast result, PDF of the spot forecast error, and the correlation matrix of the errors, V groups of K-dimensional wind power generation scenarios can be generated by taking the following steps.

where P, Q and R are the coefficient matrices of error vectors E j + 1, E j and E j − 1, respectively.

With the help of (7.7c) and (7.7d), we obtain boldsymbol{phi} (mathbf{w}) - boldsymbol{phi} (mathbf{W}) = mathbf{PE}^{j + 1} + 2mathbf{QE}^{j} + mathbf{RE}^{j - 1}, (7.8) where P, Q and R are the coefficient matrices of error vectors (mathbf{E}^{j + 1}), (mathbf{E}^{j}) and (mathbf{E}^{j - 1}), respectively.