error sum of squares

error sum of squares

[¦er·ər ¦səm əv ¦skwerz]
(statistics)
In analysis of variance, the sum of squares of the estimates of the contribution from the stochastic component. Also known as residual sum of squares.
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Source degree of freedom (df) Groups I - 1 Error N - I Total N- 1 Source Sum of Squares (SS) Groups SS(R) = [mathematical expression not reproducible] Error SS(E) = [mathematical expression not reproducible] Total SS(Total) = [mathematical expression not reproducible] Source Mean Squre (MS) Groups MS(R) = SS(R)/(I - 1) Error MS(K) = SS(E)/(N - I) Total In the ANOVA table above, SS(R) is called the regression sum of squares, SS(E) is called the error sum of squares, SS(Total) is called the total sum of squares, MS(R) is called the mean regression sum of squares, and SS(E)is called the mean error sum of squares.
Relationship between Omnibus and Post-hoc Tests: An Investigation of performance of the F test in ANOVA
(4) We compare the original quadratic PLS with the proposed robust PLS using the explained variance, as well as the predictive mean squared error and the predicted residual error sum of squares (PRESS).
Robust Nonlinear Partial Least Squares Regression Using the BACON Algorithm
One is for the group sum of squares in the numerator and one is for the error sum of squares in the denominator.
ANOVA and t-tests
The error sum of squares [SS.sub.e], defining the distribution of Y estimates around the regression function, i.e.
Methodology and precision research of wind farm power prediction
The optimum numbers of terms in the PCA models were indicated by the lowest number of factors that gave the minimum value of the prediction residual error sum of squares (PRESS) in cross validation in order to avoid over fitting in the models.
A Feasibility Study on the Potential Use of Near Infrared Reflectance Spectroscopy to Analyze Meat in Live Animals: Discrimination of Muscles
Total Sum of Squares (TSS) = Error Sum of Squares (ESS) + Regression Sum of Squares (RSS) (15)
Using excel 2013 for regression-based cost estimation: Part 1
Coefficient of determinations ([r.sup.2]), mean square error (MSE), root mean square error (RMSE), error sum of squares (SSE) and prediction sum of squares (PRESS) were calculated.
Non-destructive models to estimate leaf area on bell pepper crop/Modelos nao-destrutivos para estimar a area foliar na cultura do pimentao
Error sum of squares [SS.sub.error] = SST - [R.sub.1] - [R.sub.2].
Design and analysis of inlet manifold of a four stroke petrol engine by increasing tumble flow rate and reducing air pollution using aerofoil plate
We tested the internal validity of the models using the coefficient of determination ([R.sup.2]), mean square error (MSE), error sum of squares (SSE) and predicted residual error sum of squares (PRESS) as described in Ghoreishi et al.
Non-destructive linear model for leaf area estimation in Vernonia ferruginea Less/Modelo linear nao-destrutivo para estimativa de area foliar de Vernonia ferruginea Less
The matching data is found by minimizing the error sum of squares. The unknown data is obtained by the least squares method simply.
Multivariate methods based soft measurement for wine quality evaluation
The prediction error sum of squares PRESS is 8.35, and consequently [R.sub.2] for prediction in our experiment amounts to 0.89.
Modelling and simulation of surface roughness in face milling
To identify an optimal grouping of participants in the clustering hierarchy, the agglomeration schedule was examined to find a late stage in the hierarchy, with a relatively small number of participant clusters, where in which the error sum of squares coefficients increased dramatically at subsequent stages in the hierarchy, after relatively small increases at previous stages (Berven & Hubert, 1977).
Neurocognitive profiles of rehabilitation clients with Schizophrenia in Taiwan

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