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MSE FINDR: A Shiny R Application to Estimate Mean Square Error Using Treatment Means and Post Hoc Test Results

Plant Disease
Research synthesis methods such as meta-analysis rely primarily on appropriate summary statistics (i.e., means and variance) of a response of interest for implementation to draw general conclusions from a body of research. A commonly encountered problem arises when a measure of variability of a response across a study is not explicitly provided in the
Vinicius C. Garnica   +3 more
openaire   +2 more sources

E-Bayesian estimations of parameter and its evaluation standard: E-MSE (expected mean square error) under different loss functions

Communications in Statistics - Simulation and Computation, 2019
This paper is concerned with using the E-Bayesian method for computing estimates of Pareto index.
openaire   +1 more source

Minimum mean squared error (MSE) adjustment and the optimal Tykhonov–Phillips regularization parameter via reproducing best invariant quadratic uniformly unbiased estimates (repro-BIQUUE)

Journal of Geodesy, 2007
In a linear Gauss–Markov model, the parameter estimates from BLUUE (Best Linear Uniformly Unbiased Estimate) are not robust against possible outliers in the observations. Moreover, by giving up the unbiasedness constraint, the mean squared error (MSE) risk may be further reduced, in particular when the problem is ill-posed.
openaire   +1 more source

Reduction of Bit Error Rate (BER) and Mean Square Error (MSE) in MIMO-OFDM System Using SUI and ETU Channels

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON), 2023
Munna Khan   +2 more
openaire   +1 more source

Mean Square Error Estimation in Thresholding

IEEE Signal Processing Letters, 2011
Soosan Beheshti   +2 more
exaly  

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