B-factor predictions using different regression models
Symbolic Regression Using Compound Models
... Chapter 4 Proposed Method Preliminary experiments with standard GP methods for SR showed, that finding a sufficient symbolic model with minimal error is strongly dependent on the complexity of input dataset. Datasets ...
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The Structure of Factor Content Predictions
... are using data on 41 developed and developing countries whereas they used 10 OECD ...by factor we obtain very different results than Davis and ...the factor content of trade for their core ...
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Sorptive number prediction of highly calcareous soils at different applied tensions using regression models
... α using PTFs were sand and silt contents, BD, θ i , θ s and the most influential investigated chemical attributes were CEC/EC, OM, pH, ESP, SAR, and Ca sol ...PTFs predictions for testing dataset varied ...
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Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models
... primary models were calibrated and verified using the same calibration and validation ...downscale models for each season, the combining SAM and CANN seasonal models were built using ...
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Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models
... built using outputs from these primary models as ...downscale models, whereas the ANN model was developed using the network structure shown in Figure ...downscale models were directly ...
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Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models
... of using the combining approach in the field of rainfall-runoff forecasting have formed great motivations for the current ...circulation models (GCMs), however, up until now, they unfortunately do not seem ...
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Adaptive Partially Linear Regression Models by Mixing Different Estimates
... The APLM is illustrated using a real data example called the current population survey (CPS). The CPS data are taken from a population survey in 1985 in USA. (See Berndt, 1991). The CPS data contains 534 ...
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Predictions of Genetic Merit in Tree Breeding Using Factor Analytic Linear Mixed Models and Blended Genomic Relationship Matrices.
... for predictions of genetic merit missing genotypes is a limiting factor in terms of power and methodology for the estimation of genomic estimated breeding ...for predictions require complete genotype ...
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Wildfire Predictions: Determining Reliable Models using Fused Dataset
... IX. D ecision T ree V alidation After the Nearest Neighbor approach to classification/regression, perhaps the second most intuitive model is Decision Trees. There are many possible trees can be used to organize ...
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Trauma scoring models using logistic regression.
... Alternate survivors and non-survivors were placed into the training and test data set. An alternative method of data splitting is to perform a chronological split of the data accepting that the training and test data ...
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Confidence bands in quantile regression and generalized dynamic semiparametric factor models
... Quantile Regression and Bootstrap Confidence Bands with classic (mean) ...to different genders, labour union status, nationalities and inequality analysis amongst other things will definitely bring more ...
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Using DNase I hypersensitivity Data for Transcription Factor Binding Predictions
... transcription factor binding prediction using various high-throughput sequencing data has made significant progress recently, there is still an urgent demand to develop novel computational methods for ...
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Determination Of Several Plant Characteristics Affecting Yield Per Decare In Peanut Using Different Regression Models
... investigated. Regression model was used in this ...the regression model were found to be significant with ordinary least squares (OLS) method (P < ...the regression model predicted by the OLS method, ...
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Regression models
... truncated regression models fitted with ...(NWP) models that take the current state of the atmosphere and compute future weather by numerically simulating the most important atmospheric ...numerical ...
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Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models
... three different methods were used to define macroecological constraints, resulting in models with the stacked probabilities from SDMs (h; pS-SDM) and two different macroecological models ...
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Solving Regression Problems Using Competitive Ensemble Models
... ensemble models in many problem domains has increased significantly in the last few ...their predictions are aggregated to obtain the improved ...the models in the ...domain regression ...
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Robust mixture regression models using t-distribution
... Case I is used to test the efficiency of different estimation methods compared to the traditional MLE when the error is exactly normally distributed and there are no outliers. Case II is a heavy-tailed ...
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Construction of insurance scoring system using regression models
... Construction of scoring system requires the negative estimates to be converted into positive values and the conversion process can be performed by using the following procedures. First, the smallest negative ...
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A priori ratemaking using bivariate Poisson regression models
... linear models, and here the Poisson regression model constitutes the most widely accepted ...two different types of ...Poisson regression models, suitable for paired count data ...
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A priori ratemaking using bivariate poisson regression models
... linear models, and here the Poisson regression model constitutes the most widely accepted ...two different types of ...Poisson regression models, suitable for paired count data ...
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