Semi–parametric and model–based approaches
Efficiency Analysis of Rural Hospitals: Parametric and Semi-parametric Approaches
... diagnosis related group (DRG) under the Medicare prospective payment system (PPS). 1 Previous research showed that Medicare cost-based reimbursement gave hospitals few incentives to control their costs and ...
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Semi-Parametric Estimation of a Logit Model
... There are several possible directions for future research. First, as noted in several places in the paper it may well be possible to derive the same results under somewhat weaker condi- tions. Second, it seems likely ...
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Short-term load forecasting based on a semi-parametric additive model
... • the day of year effect IV. F ORECASTING RESULTS According to the Annual Electricity Market Performance Review 2008, published by Australian Energy Market Commission (AEMC) [27], the historical demand forecasting ...
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A semi-parametric model for circular data based on mixtures of beta distributions
... mixture model to Bernstein polynomials which have been developed as an approach to esti- mating densities with support [0, 1] by ...mixture model and we fit our model to two, well known, real data ...
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Comparing parametric and semi-parametric approaches for bayesian cost-effectiveness analyses in health economics
... A semi-parametric approach In recognising the extreme complexity of cost distributions (the construction of cost data as a weighted sum of different resource counts implies that cost distributions are ...
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A Semi Analytical Parametric Model for Dependent Defaults
... models based on Marshall- Olkin copula that have been in use in reliability ...a parametric setting. A semi-analytical representation of the default probability distribution for a homogeneous ...
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spa: Semi-Supervised Semi-Parametric Graph-Based Estimation in R
... several approaches in existence to perform the difficult task of semi-supervised classi- fication with graphs, including mini-cut algorithms (Blum and Chawla 2001; Kondor and Laf- ferty 2002), directed ...
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Dynamic semi-parametric factor model for functional expectiles
... overparametrized model, which captures almost any behaviour or trend, ...the model and the number of dependent variables by lasso ...proposed model for estimation and forecasting of daily tempera- ...
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A (semi-)parametric functional coefficient autoregressive conditional duration model
... (ACD) model that abound in the litera- ...sion based on self-exciting threshold ACD processes, whereas Meitz and Ter¨asvirta (2006) propose the smooth transition and the time-varying ACD ...models ...
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Semi-parametric Regression under Model Uncertainty: Economic Applications
... is based on a multiplicative parameter expansion strategy which introduces only partially identifiable working parameters to enable simultaneous selection or deselection of large coefficient ...
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Bayesian inference for a semi parametric copula based Markov chain
... However, for discrete data types such methods can create computational problems (algorithm failing to converge) and induce bias. Hoff (2007) proposes a technique for cross-sectional data of mixed type ...
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Statistical inference for inequality measures based on semi-parametric estimators
... The remedial action can be either a trimming of the extreme data or a modification of the (traditional) estimator to make it more robust to extreme observations. In this thesis we follow the second option, modifying the ...
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A semi-parametric regression model for analysis of middle censored lifetime data
... used semi-parametric regression model is the well known proportional haz- ards model by David ...hazards model, one may refer to Kalbfleisch and Prentice (2011) and Lawless ...
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Semi parametric regression model for survival data: graphical visualization with R
... hazards model depends on regression coefficients, significance level and prevalence of covariate ...full model including all available covariates is ...
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A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model
... (MPH) model for duration data that was indepen- dently introduced by Lancaster (1979) and Manton, Stallard, and Vaupel (1981) has been used quite frequently in empirical work, the standing of this model ...
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A (Semi)Parametric Functional Coefficient Logarithmic Autoregressive Conditional Duration Model
... (ACD) model that abound in the literature (Engle and Russell, ...version based on threshold ACD processes, whereas Meitz and Ter¨asvirta (2006) propose the smooth transition and the time-varying ACD ...
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Semi and non semi parametric models for reliability analysis
... hazard model most commonly used multivariable approach for analysing survival time data in medical ...a model with four covariates, namely, recurrence of the disease, age of the woman, duration of ...
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Skin Detection Based on Color Model and Low Level Features Combined with Explicit Region and Parametric Approaches
... color model and representations of the human image in color model is one of major module to detect the skin ...is based on the individual pixels and selection of the pixels to detect the skin part in ...
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Optimization-based approaches to non-parametric extreme event estimation
... specific parametric curve to fit the tail data that is only justified in large-threshold situations, the model bias is ...from parametric to non- parametric estimation, and needs to be ...
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Long-rang Correlation for USD/EUR based on Semi-parametric Estimation
... forward semi-parameter estimation methods (Standard GPH Method, Tapered GPH Method), and concluded through comparable analysis that: In the conditions of V using T ...
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