Nonparametric Methods
Semiparametric and nonparametric methods for evaluating risk prediction markers in case-control studies
... Although methods have been developed to estimate predictiveness curves from cohort studies, most studies to evaluate novel risk prediction markers employ case-control ...and nonparametric methods ...
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Statistics review 6: Nonparametric methods
... Normally distributed, whereas the sign test only requires that they are independent of one another. Alternatively, the dis- crepancy may be a result of the difference in power provided by the two tests. As a rule, ...
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Nonlinear time series: semiparametric and nonparametric methods
... and methods used have been based initially on parametric non- linear or nonparametric time series ...related methods may be too restrictive in many ...various nonparametric techniques being ...
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Investigating the Factors Affecting Energy Consumption in the Iranian Agricultural Sector Using Parametric and Nonparametric Methods
... Iran, as a developing country with enormous energy resources, extensive oil reservoirs and large mineral deposits, is an example of growth based on over-exploitation of natural resources (Barati Malayeri and Hoori ...
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Empirical comparisons in short term interest rate models using nonparametric methods
... Empirical comparisons in short-term interest rate models using nonparametric methods Arapis, Manuel and Gao, Jiti The University of Western Australia, The University of Adelaide... feder[r] ...
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Hybrid model using logit and nonparametric methods for predicting micro-entity failure
... traditional methods, such as discriminant analysis (DA) and logistic regression ...black-box methods and, therefore, are difficult, if not impossible, to ...
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Bayesian Nonparametric Methods For Causal Inference And Prediction
... Our approach in modeling the relationship between Y and X targets the conditional mean of Y given X , which we denote as ω(·). There is large statistical literature focused on modeling ω(·) flexibly; we review some of ...
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Composing Deep Learning and Bayesian Nonparametric Methods
... Bayesian methods are good at handling discrete and bursty latent structures in data through explicit probabilistic ...Bayesian nonparametric (BNP) methods are naturally suited for large scale ...
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Towards scalable Bayesian nonparametric methods for data analytics
... 6.1. Motivation 120 using topic models, e.g. LDA or HDP. Now each document is considered as an input data point for some clustering algorithm. (Elango and Jayaraman, 2005) used LDA combined with K-means to cluster images ...
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Model of Robust Regression with Parametric and Nonparametric Methods
... of nonparametric estimators are better than OLS in presence of outliers in X- direction and XY- direction, it seems less better in estimating intercept when we have no outliers, thus those estimators is not robust ...
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Healthcare reform in Italy: an analysis of efficiency based on nonparametric methods
... Thus, to take into account of differences in quality and quantity in the health services offered, we introduced the variables interregional patients inflow and outflow, which describe pa[r] ...
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Lecture 2 ESTIMATING THE SURVIVAL FUNCTION. One-sample nonparametric methods
... We could use the same approach by grouping the event times into intervals (say, one interval for each month), and then counting up the number of deaths (events) in each to esti- mate the[r] ...
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An asymptotic analysis of distributed nonparametric methods
... other nonparametric models, such as nonpara- metric regression and density ...compare methods that were originally intro- duced in different ...distributed methods, we believe that the conclusions ...
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Tax Reform Evaluation Using Nonparametric Methods: Sweden 1980 - 1991
... When discussing the effects on the income distribution we do this for two types of income units. First of all we do it for married or cohabiting men. Using the nonparametric labor supply function we can study how ...
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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] ...
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Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
... and nonparametric models for the optimal hedge ratio and find some evidence which is not presented in the previous ...the nonparametric technique models the marginal ...GARCH-class methods, our ...
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Bayesian Nonparametric Methods for Testing Shape Constraints
... Much literature has focused on the estimation of shape constrained regression functions. Sampling from a truncated multivariate distribution subject to multiple linear inequality con- straints is usually encountered in ...
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Assessing the adverse effects of interbank funds on bank efficiency through using semiparametric and nonparametric methods
... intelligence methods, also recognized as data mining methods, that deal with the grouping of a set of entities are cluster analysis (clustering) and classification (Han et ...
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Nonparametric and semiparametric methods in medical diagnostics
... curves, nonparametric approaches have been proposed to estimate the ...fully nonparametric approach to the comparison of correlated ROC curves by using the theory on ...two nonparametric ...
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Nonparametric Tests
... “It is fashionable to claim that nonparametric methods were first used when J. Arbuthnot (1710) found that in each year from 1929 to 1710 the number of males christened in London exceeded the number of ...
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