[PDF] Top 20 Estimating rate equations using nonparametric regression methods
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Estimating rate equations using nonparametric regression methods
... Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalized cross-vaslidation. Numerische Mathematik 31, 377-403[r] ... See full document
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A nonparametric approach for quantile regression
... direct nonparametric quantile regression method which uses the ideas of nonparametric kernel density estimation and nonparametric kernel ...existing nonparametric quantile ... See full document
14
Mapping Quantitative Trait Loci by an Extension of the Haley–Knott Regression Method Using Estimating Equations
... HK methods (H aley and K nott 1992; X u 1998a,b; K ao 2000), and in many cases the two methods provide almost identical parameter estimates and test ...two methods by computer simulations, found that ... See full document
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Using generalized estimating equations with regression splines to improve analysis of butterfly transect data
... latter’s regression coefficients describe the average population response and only describe the covariance among repeated observations (do not attempt to explain ... See full document
151
Estimating the expected value of sample information using the probabilistic sensitivity analysis sample: A fast, nonparametric regression-based method.
... One option for computing EVSI is to assume that the incremental net benefit is Normally distributed with parameters that are known functions of study sample size. Under this assumption, EVSI can be cal- culated ... See full document
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Convergence rates for regularized solutions of integral equations from discrete noisy data
... Method of regularization, approximate solution of integral equations, rates of convergence, nonparametric regression, Abel's equation, particle size distribution.... where the £'s are ra[r] ... See full document
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Measuring exchange rate flexibility by regression methods
... After estimating equation (2), the authors focus on the estimates of the individual coefficients b, c and d. They identify a currency as floating only if none of them is significantly different from zero. This ... See full document
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Estimating Lyapunov exponents with nonparametric regression
... For a sample size in the range of 2000-2500 and no measurement error we evaluated the performance of the four approximation methods described in Section 4 ( Local Spline, Radial Basis, N[r] ... See full document
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Generalized Estimating Equations for Repeated Measures Logistic Regression in Mosquito Dose Response
... studies and when the interest is in the speed of kill, one has to move on to alternative method which accounts for the correlation in the data while estimating lethal time and of such methods is the ... See full document
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Seasonal Decomposition for Geographical Time Series using Nonparametric Regression
... linear trend and seasonal cycles that repeat with a 12-month period. We assume an additive model and try the two different methods introduced in the previous section. For ST L decomposition, there is a default ... See full document
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Constrained nonparametric estimation of input distance function
... econometric methods, ...propose estimating a technology without a parametric functional form via nonparametric kernel econometric ...the nonparametric regression function such that the ... See full document
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Estimation of Regression Model Using a Two Stage Nonparametric Approach
... restricted regression based on the theo- retical shape or stipulated shape of the empirical ...practical methods which provide adequate information about the regression with many ...for ... See full document
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A Comparative Analysis of Generalized Estimating Equations Methods for Incomplete Longitudinal Ordinal Data with Ignorable Dropouts
... logistic regression models for ordinal responses ...other methods like mixed models can be ...logistic regression models have been found to be most useful when dealing with ordinal data ...logistic ... See full document
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Estimation of Nonparametric Regression Models with Measurement Error Using Validation Data
... of estimating a function g in nonparametric regres- sion model when only some of covariates are measured with errors with the assistance of validation ...convergence rate of this ... See full document
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Nonparametric estimating equations for circular probability density functions and their derivatives
... In a second experiment, we estimate various densities by selecting smooth- ing degree by simple least squares cross-validation. Our population models are represented in Figure 3. Other than the standard von Mises, we ... See full document
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Nonparametric bootstrapping for multiple logistic regression model using R
... Bootstrapping is a general approach to statistical inference based on building a sampling distribution for a statistic by resampling from the data at hand. Efron (1979) discussed bootstrap procedure that can be applied ... See full document
5
Application of Nonparametric Quantile Regression to Estimating Value at Risk.
... the nonparametric regression model large enough so that the estimates will interpolate every observation: when K = N − 2, λ = 0 or h is small ...a nonparametric model is to discover the associations ... See full document
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Bayesian Nonparametric Covariance Regression
... function using a bandwidth of ...information. Using a much larger bandwidth of ...Bayesian nonparametric method is able to maintain a local description of the data while sharing information across ... See full document
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Nonparametric circular quantile regression
... where ˆ F λ,κ (i) ( · ) is the smoothed estimate (1) of the conditional CDF using all the data except the ith observation, with smoothing parameters κ and λ. There are two points to note here. Firstly, the ... See full document
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Estimating adjusted prevalence ratio in clustered cross-sectional epidemiological data
... on regression models have been ...logistic regression model: the conditional method where a standard value, usually the mean, is chosen for the covariates and the prevalence is computed for each comparison ... See full document
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