Parametric and nonparametric methods
Investigating the Factors Affecting Energy Consumption in the Iranian Agricultural Sector Using Parametric and Nonparametric Methods
... Thus, studying energy consumption in all economic sectors, especially in agriculture, is of great importance. Studying energy consumption based on new and efficient scientific models would help us find ways to deal with ...
16
On Parametric and Nonparametric Methods for Dependent Data
... popular nonparametric estimator of the covariance function of Hall and Patil (1994) for irregularly spaced spatial data will have a nontrivial bias under PID asymptotic structure and hence, will be ...
100
Model of Robust Regression with Parametric and Nonparametric Methods
... (LAD); nonparametric estimators contains "complete Thiel's estimator (CTH) and incomplete Thiel's estimator (ITH) with Conover's estimator for intercept"; suggested nonparametric estimator contains ...
13
Parametric and Nonparametric Methods for SAR Patch Scene Categorization
... All classes had very simi- lar recognition rates (approx. Classes C6-Urban-02, C15-Airstrip, and C20-Ambiguities had lower recognition rates. The GLCM features gave very low recogni- tio[r] ...
12
Evaluation of Parametric and Nonparametric Statistical Methods in Genomic Prediction
... the parametric and nonparametric methods, but GS could be influenced by many factors, such as number of individuals, number of markers, number of QTL, the proportion of epistatic variance relative to ...
141
Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures
... ABSTRACT Parametric and nonparametric methods have been developed for purposes of predicting ...These methods are based on retrospective analyses of empirical data consisting of genotypic and ...
22
Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures
... ABSTRACT Parametric and nonparametric methods have been developed for purposes of predicting ...These methods are based on retrospective analyses of empirical data consisting of genotypic and ...
21
Parametric and Nonparametric Regression with Missing X’s—A Review
... Whereas parametric regression has been investigated extensively, nonparametric methods haven’t been considered within this context so ...of parametric methods. Little emphasis has been ...
31
Nonparametric and Parametric Measures of Scale Elasticity: A Comparative Evaluation
... various parametric as well nonparametric ...these methods in order to shed light on what seems to be missing, and then to proceed by developing an empirically de- manding ecompassing measure of scale ...
38
Nonparametric predictive inference with parametric copula for survival analysis
... new nonparametric methods for predictive inference for survival analysis involving a future bivariate ...bivariate Nonparametric Predictive Inference (NPI) for the marginals with parametric ...
6
Economic applications of nonparametric methods
... The parametric specification (say through mixtures, dummies, etc.) would require ad-hoc assumptions. Moreover semiparametric models and estimation methods, where un- kn[r] ...
267
Parametric and Nonparametric Volatility Measurement
... econometric methods and models take on a very different, conditional, flavor when volatility is properly recognized to be ...tightly parametric, but the recent literature has moved in less ...
68
A simulation-based comparison between parametric and nonparametric estimation methods in PBPK models
... compare parametric and nonparametric estimation methods in the context of PBPK modeling using simulation ...the parametric method, and a functional analytical approach to estimate the ...
99
Modelling via normalisation for parametric and nonparametric inference
... MCMC methods consist of constructing a Markov Chain (i.e. a chain where each updating step depends only on the previous iteration of the chain) that has the desired posterior distribution of all parameters in the ...
207
A Paradox of Inconsistent Parametric and Consistent Nonparametric Regression
... which nonparametric regression is consistent whereas parametric regression is inconsistent even when the true regression functional form is known and used in ...regression methods turn out to have a ...
32
MatchIt: Nonparametric Preprocessing for Parametric Causal Inference
... Many methods that offer this preprocessing are included here, including exact, subclassification, nearest neighbor, optimal, and genetic ...these methods the propensity score — defined as the probability of ...
28
Some Recent Developments in Parametric and Nonparametric Regression Models.
... The majority of variable selection methods revolve about the notion of selection con- sistency and examine how often a method identifies the correct model. However, in the modern world of high-dimensional data, a ...
79
Comparison of Parametric and Nonparametric Techniques for Water Consumption Forecasting
... In the state space approach for the exponential smoothing methods, the error terms are smoothed. The corresponding models are called innovation state space models. Note that it is an innovation because all ...
7
Wind power forecasting by nonparametric and parametric time series models
... several methods reported in the literature for computing the intervals depending on the statistic of interest and the sample ...common parametric method for fixing the intervals is the one based on the ...
83
Asymptotic behavior of some Bayesian nonparametric and semi-parametric procedures
... Density estimation, which is also relevant in various applications such as cluster analysis and robust estimation, is a fundamental nonparametric inference problem. In Bayesian approach to density estimation, a ...
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