squared error
Convex vs Non-Convex Estimators for Regression and Sparse Estimation: the Mean Squared Error Properties of ARD and GLasso
... We study a simple linear regression problem for grouped variables; we are interested in methods which jointly perform estimation and variable selection, that is, that automatically set to zero groups of variables in the ...
36
Estimating a Bounded Normal Mean Relative to Squared Error Loss Function
... mean X , is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. In many practical situations, is known in advance to lie in an interval, say [ m ...
10
An Empirical Study on Mushroom Disease Diagnosis:A Data Mining Approach
... of error rate ...of error rates namely Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE), Root Relative Squared Error (RRSE) ...
6
Antenna arrays in multi user detection of spread spectrum signals
... frame error rates to be unacceptably ...the error rates increase with the number of ...mean-squared error due to MAI, and show how the frame error rate increases with the number of ...
6
“MODELING AND FORECASTING OF THE STOCK MARKET VOLATILITY OF S&P CNX NIFTY 50 INDEX OF INDIA USING GARCH FAMILY MODELS”
... Mean Squared Error (RMSE), the Mean Absolute Error (MAE), the Mean Absolute Percent Error (MAPE) and the Theil Inequality Coefficient ...the error measurements is deliberated to be the ...
13
Bayes rules for optimally using Bayesian hierarchical regression models in provider profiling to identify high-mortality hospitals
... patients, administrators, and funders; to debate the trade- offs that have been explicitly incorporated into the analy- ses described in this study. Once this has been done, report cards can be explicitly produced using ...
11
Rates of convergence of some estimators in a class of deconvolution problems
... Key Words and Phrases: Deconvolution, density estimation, mean squared error, measurement error, rates of convergence, uniform convergence.. 1 Work supported by NSF Grant DMS-86-13681A[r] ...
10
Confidence intervals for the estimated smoothing parameter in nonparametric regression
... Confidence intervals are constructed for the smoothing parameter that minimizes average squared error using the asymptotic distribution of the cross-validation function and by a version [r] ...
41
Bayesian Analysis of Record Statistics Based on Generalized Inverted Exponential Model
... Recently, there has been a growing interest in the study of inference problems associated with record values and record ranked set samples via the Bayesian approach. The Bayesian estimation for the GIED based on URRSS ...
13
Analysing the temporal dynamics of model performance for hydrological models
... Dawson et al. (2007) assembled 20 performance measures used in hydrology into a test suite. This test suite includes the Nash-Sutcliffe coefficient of efficiency CE, several mea- sures based on the absolute or ...
20
Two-stage estimation to adjust for treatment switching in randomised trials: A simulation study investigating the use of inverse probability weighting instead of re-censoring
... In this study we used the same simulation study design as in our previous study [18], but extended it to investi- gate whether the TSEipcw method results in an im- provement in performance compared to TSE with and ...
20
Forecasting Spare Parts Demand Using Statistical Analysis
... Mean squared error (MSE), mean absolute deviation (MAD) and mean error (ME), where the results showed close performance for all the methods associated with their optimal parameters and the frequency ...
8
Fault Classification with Artificial Neural Networks based on the Application of Teager Energy Operator
... In [3] current signals are used as input parameters in ANN training using Back Propagation algorithm for diagnosis of the fault in a distributed motor network. Different number of nodes where tested in network structure ...
6
Adaptive digital predistortion linearisation for RF power amplifiers
... Development of linear modulation schemes has opened the way for spectrally efficient, high speed digital communication systems for voice and data applications. A trend has been to develop utra wide and wide bandwidth ...
5
Bayesian inference on reliability in a multicomponent stress-strength bathtub-shaped model based on record values
... In the literature, there are a well-developed estimation techniques for the reliability assessment in multicomponent stress-strength models when the information about all the experimental units are available. However, in ...
14
Empirical Bayes with a changing prior
... optimal procedures are then established for both the two action problem under linear loss and the squared error loss estimation problem... Rates of convergence to optimality for..[r] ...
164
NN.ppt
... BP employs gradient descent to attempt to minimize the squared error between the network output values and the target values for these outputs. Two stage learning[r] ...
57
Deconvolution based score tests in measurement error models
... This is noteworthy in the case of normal measurement error, where the squared error rate of convergence for estimating a density is of order {log(n)}-2, while that for estimating m(w) is[r] ...
11
Soil Thermal Diffusivity of a Gleyic Solonetz Soil Estimated by Different Methods in the Brazilian Pantanal
... Using the soil thermal diffusivity estimated by ampli- tude method as reference was computed mean absolute error-MAE and the root mean squared error-RMSE be- tween phase methods, arctangent and ...
8
Comparative Studies on Evolutionary Computational Techniques for Speed Control of A DC Motor
... absolute error and squared ...ITSE error model. Similarly for other error models also even for the same two different speeds it is observed that lesser number of generations are required in ...
15