In statistics the mean squared prediction error (MSPE), also known as mean squared error of the predictions, of a smoothing, curve fitting, or regression...

In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures...

processes. Root mean square Mean absolute error Average absolute deviation Mean signed deviation Mean squared deviation Squared deviations Errors and residuals...

in the sense that the least squares approach is related to the mean squared error, the equivalent for mean absolute error is least absolute deviations...

equalizer "Mean Squared Error (MSE)". www.probabilitycourse.com. Retrieved 9 May 2017. Moon and Stirling. Johnson, D. "Minimum Mean Squared Error Estimators"...

zero. Percentage error Mean absolute percentage error Mean squared error Mean squared prediction error Minimum mean-square error Squared deviations Peak...

The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation (MAPD), is a measure of prediction accuracy of a forecasting...

In mathematics, the root mean square (abbrev. RMS, RMS or rms) of a set of numbers is the square root of the set's mean square. Given a set x i {\displaystyle...

arises in the expression mean squared error (MSE). The mean squared error of a regression is a number computed from the sum of squares of the computed residuals...

Mean absolute error Mean absolute percentage error Mean squared error Root mean squared error Armstrong, J. S. (1985) Long-range Forecasting: From Crystal...

a_{0}=-1} . On the other hand, if the mean square prediction error is constrained to be unity and the prediction error equation is included on top of the...

mean. In regression analysis, the term "standard error" refers either to the square root of the reduced chi-squared statistic or the standard error for...

true error variance σ2 is replaced by an estimate, the reduced chi-squared statistic, based on the minimized value of the residual sum of squares (objective...

has a smaller mean squared error. In practice s2 is used more often, since it is more convenient for the hypothesis testing. The square root of s2 is...

MAE=MAD={\frac {\sum _{t=1}^{N}|E_{t}|}{N}}} Mean squared error (MSE) or mean squared prediction error (MSPE):   M S E = M S P E = ∑ t = 1 N E t 2 N...

sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum of the squares of residuals...

continuously distributed, the mean squared error, root mean squared error or median absolute deviation could be used to summarize the errors. When users apply cross-validation...

terms of metrics such as correlation, root mean squared error, mean absolute error, relative mean absolute error, bias, and the Brier score, among others...

y_{n})\}} . We make "as well as possible" precise by measuring the mean squared error between y {\displaystyle y} and f ^ ( x ; D ) {\displaystyle {\hat...

used to estimate the population mean μ and population standard deviation σ of the underlying population, while prediction intervals may be used to estimate...

Forecast errors can be evaluated using a variety of methods namely mean percentage error, root mean squared error, mean absolute percentage error, mean squared...

out-of-sample mean squared error, also known as the mean squared prediction error, is substantially higher than the in-sample mean square error, this is a...

data Reduced chi-squared statistic Robust standard deviation Root mean square Sample size Samuelson's inequality Six Sigma Standard error Standard score...

the coefficient of determination, denoted R2 or r2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is...

accuracy is very closely related to the mean squared error (MSE) method which is just the average squared error of the forecasts. Although these methods...

statistic is chi-squared distributed under the null hypothesis, specifically Pearson's chi-squared test and variants thereof. Pearson's chi-squared test is used...

of the least squares cost function as in ridge regression (L2-norm penalty) and lasso (L1-norm penalty). Use of the Mean Squared Error (MSE) as the cost...

example, the method of ordinary least squares computes the unique line (or hyperplane) that minimizes the sum of squared differences between the true data...

}})^{2}.} An Estimator found by minimizing the Mean squared error estimates the Posterior distribution's mean. In density estimation, the unknown parameter...

regularization Matthews correlation coefficient Mean shift Mean squared error Mean squared prediction error Measurement invariance Medoid MeeMix Melomics...