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Exact(7)
DOF shows the total number of model terms, including intercept minus one while mean square estimates the model variance, calculated by the model sum of squares divided by model degrees of freedom.
The Kalman filter can be either viewed as a minimum mean square estimates or a maximum posterior estimates.
The mean square estimates for genotype were over 60x the mean square errors for these traits (Table 2).
The genotype mean square estimates for the remaining 7 traits ranged from 5 to 32 times the mean square error.
The mean square estimates to calculate the ICC coefficients were obtained from a random effects 2-way analysis of variance with repeated measures [ 50].
The degrees of freedom, sum of squares, mean square estimates, F and P values associated with the basic test described above, and the analysis of covariance using statistical software are exactly the same.
Similar(53)
In order to compensate the location error due to the NLOS condition, we suggest a location estimation approach, which combines the minimum mean square estimate (MMSE) [10] and the Min-max method [11].
After adding three paths, the model had a good fit to the data (comparative fit index=0.94; root mean square estimate of error=0.06).
minimum mean square estimate.
Taking advantage of the Gaussian properties, the authors design a Kalman-like particle filter (KLPF) where a group of Kalman filters are processing in parallel to obtain minimum mean square estimate of the state conditioned on perfect observations.
Linear prediction is the problem of finding the minimum mean square estimate of using a linear combination of the past signal values from to The most commonly used forward one step Finite Impulse Response (FIR) linear predictor of order is given by (4).
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