nonparametric approach
Modeling U.S. Inflation Dynamics : A Bayesian Nonparametric Approach
... This paper uses an infinite hidden �arkov model �IHMM) to analyze U.S. in- flation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling ...
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Estimation of Regression Model Using a Two Stage Nonparametric Approach
... known, we use the nonparametric approach to estimate one-dimensional and multi-dimensional density estimates. Here, for the choice of kernels and selection of band- widths, we follow the general guideline ...
10
Mean VaR portfolio optimization: a nonparametric approach
... parametric approach (variance-covariance), nonparametric approach (historical simulation) and Monte Carlo simulation methods [40, ...the nonparametric (historical simulation) method makes no ...
38
Efficiency assessment of Portuguese municipalities using a conditional nonparametric approach
... this nonparametric approach, we can avoid the strong assumptions on the specification of the estimated production function required by traditional two-stage ...
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Automatically Determining a Proper Length for Multi Document Summarization: A Bayesian Nonparametric Approach
... 2012). Some global optimization algorithms are de- veloped, instead of greedy search, to select the best overall summaries (Nenkova and McKeown, 2012). One approach to global optimization of summariza- tion is to ...
11
A nonparametric approach for quantile regression
... This approach may be restricted by the linear model ...direct nonparametric quantile regression method with five-step ...direct nonparametric quantile regression model fits the data set better than ...
14
Nonparametric approach to portfolio diversification: the case of Australian equity market
... using nonparametric and nonlinear methods is missing (particularly in Australian context as well as in terms of style and size ...and nonparametric unit root tests and nonparametric cointegration in ...
27
A Bayesian Nonparametric Approach for Mapping Dynamic Quantitative Traits
... We evaluate performance of our methods with both simu- lated and real data examples. Our simulation analyses are largely based on the simulated data from the QTLMAS2009 workshop (Coster et al. 2010), and the real data ...
38
The predictability of asset returns in the BRICS countries: a nonparametric approach
... model. Nonparametric methods apply no assumption to the functional form, ...applying nonparametric regression techniques to emerging market economies, specifically the major trading partners, are expected ...
26
Efficiency of electricity use and productivity change of electricity in China: A nonparametric approach
... In order to have a more accurate and clear picture about the productivity change and efficiency of electricity, the results from our model are presented in following tables and figure.3 [r] ...
9
Spatial environmental efficiency indicators in regional waste generation: A nonparametric approach
... The last strand in the literature use undesirable outputs as inputs. This strand argues that if an undesirable output is used as input then it works as a proxy for the use of the environment in the form of its ...
30
A computationally efficient nonparametric approach for changepoint detection
... an approach proposed by Zou et ...This approach defines the best segmentation for a data set as the one which minimises a penalised cost function, with the cost function defined in term of minus a ...
32
A nonparametric approach for mapping quantitative trait loci.
... Parametric interval mapping allows efficient de- tection and localization of QTLs for normally distrib uted traits, while keeping the false positive rate low through the[r] ...
8
Growth and the pollution convergence hypothesis: A nonparametric approach
... This paper investigates the income-pollution link within a β-type regression setting. A dynamic relationship involving pollution growth, past pollution levels, past GDP levels and GDP growth is derived from a growth ...
42
Does the Box Cox transformation help in forecasting macroeconomic time series?
... a nonparametric approach for estimating the optimal transformation parameter based on the frequency domain estimation of the prediction error variance, and also conduct an extensive recursive forecast ...
23
Hierarchical Cluster Analysis Histogram Thresholding with Local Minima
... In this study, we propose a method which is based on "Image segmentation by histogram thresholding using hierarchical cluster analysis"/HCA/ and "A nonparametric approach for histogram ...
6
Robust Sample Survey Inference via Bootstrapping and Bias Correction: The Case of the Ratio Estimator
... the nonparametric alternatives NP(1X-Hu/6) and W(1X-Hu/2-Hu/6) based on smoothing against the population ...the nonparametric estimator based on smoothing against the population X-ranks, NP(1R-Hu/6), ...
21
Review of Non Parametric Regression and its application using SAS software
... a nonparametric regression approach when the standard regression model is not ...a nonparametric approach might not only be beneficial, but ...analysis. Nonparametric methods provide an ...
18
Demand for Meat; Seprability and Structural changes (A Nonparametric Analysis)
... the nonparametric approach avoids the specification bias likely to arise due to arbitrarily selected functional forms or the pre-testing inherent in specification searches [Eales and Unnevehr ...The ...
18
Bayesian Inference about Some Geometric Aspects of Nonparametric Functions.
... some nonparametric functions in various settings and obtain the corresponding contraction rates for level ...classical nonparametric regression ...and nonparametric regression using B-splines series ...
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