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We propose two nonparametric transition density-based speciÞcation tests for continuous-time diffusion models. In contrast to marginal density as used in the literature, transition density can capture the full dynamics of a diffusion process, and in particular, can distinguish processes with...
Persistent link: https://www.econbiz.de/10009621413
Appraisals are needed for decision-making and for performance evaluation. Knowledge on the accuracy of valuation methods is of general interest for banks and investors. We assess the accuracy of the German Regulation on Valuation with monthly data on appraisals and prices for commercial...
Persistent link: https://www.econbiz.de/10009625798
Persistent link: https://www.econbiz.de/10001919333
for the production function is discussed. -- Nonparametric Regression ; Additive Models ; Testing Additivity ; Derivative …
Persistent link: https://www.econbiz.de/10009574875
Persistent link: https://www.econbiz.de/10009576213
This methodological paper discusses the application of "adaptive" non-parametric procedures for estimating regression …
Persistent link: https://www.econbiz.de/10009577458
A recipe is provided for producing, from a sequence of procedures in the Gaussian regression model, an asymptotically … observations from a Gaussian discrete regression model. -- asymptotic minimax risk ; Nonparametric experiments ; deficiency …
Persistent link: https://www.econbiz.de/10009578013
This paper proposes a nonparametric test of the non-convexity of a smooth regression function based on least squares or …
Persistent link: https://www.econbiz.de/10009578020
This paper is the attempt to summarize the state of art in additive and generalized additive models (GAM). The emphasis is on approaches and numerical procedures which have emerged since the monograph of Hastie and Tibshirani (1990) although reconsidering certain aspects of their work. Apart...
Persistent link: https://www.econbiz.de/10009578569
Models are studied where the response Y and covariates X, T are assumed to fulfill E(Y|X; T) = G{XT β + α + m1(T1) + … + md(Td)}. Here G is a known (link) function, β is an unknown parameter, and m1, …, md are unknown functions. In particular, we consider additive binary response models...
Persistent link: https://www.econbiz.de/10009578571