Search Results - subject:"parameter estimation"

Parameter estimation for binomial AR(1) models with applications in finance and industry

Weiß, Christian; Kim, Hee-Young - In: Statistical Papers 54 (2013) 3, pp. 563-590

Methods for analyzing and modeling count data time series are used in various fields of practice, and they are particularly relevant for applications in finance and economy. We consider the binomial autoregressive (AR(1)) model for count data processes with a first-order AR dependence structure...

Persistent link: https://www.econbiz.de/10010998550

A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions

Hurn, A.S.; Lindsay, K.A.; McClelland, A.J. - In: Journal of Econometrics 172 (2013) 1, pp. 106-126

conditioning procedure is developed that allows parameter estimation in the absence of proxies. …

Persistent link: https://www.econbiz.de/10010594960

A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance

Corradi, Valentina; Swanson, Norman - Department of Economics, Rutgers University-New Brunswick - 2013

that allows for parameter estimation error in certain contexts, and White (2000) who develops testing methodology suitable …, both under vanishing and non-vanishing parameter estimation error, with focus on the construction of valid bootstrap … critical values in the case of non-vanishing parameter estimation error, under recursive estimation schemes, drawing on Corradi …

Persistent link: https://www.econbiz.de/10010678606

Parameter estimation of solar cells and modules using an improved adaptive differential evolution algorithm

Jiang, Lian Lian; Maskell, Douglas L.; Patra, Jagdish C. - In: Applied Energy 112 (2013) C, pp. 185-193

. Comparisons with existing methods for solar cell and module parameter estimation are presented using both synthetic and …

Persistent link: https://www.econbiz.de/10010702500

Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification

Bachoc, François - In: Computational Statistics & Data Analysis 66 (2013) C, pp. 55-69

The Maximum Likelihood (ML) and Cross Validation (CV) methods for estimating covariance hyper-parameters are compared, in the context of Kriging with a misspecified covariance structure. A two-step approach is used. First, the case of the estimation of a single variance hyper-parameter is...

Persistent link: https://www.econbiz.de/10010666180

A survey of recent advances in forecast accuracy comparison testing, with an extension to stochastic dominance

Corradi, Valentina; Swanson, Norman R. - 2013

Persistent link: https://www.econbiz.de/10009766717

A simulation based specification test for diffusion processes

Bhardwaj, Geetesh; Corradi, Valentina; Swanson, Norman R. - 2005

This paper makes two contributions. First, we outline a simple simulation based framework for constructing conditional distributions for multi-factor and multi-dimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be...

Persistent link: https://www.econbiz.de/10010266342

Nonparametric bootstrap procedures for predictive inference based on recursive estimation schemes

Corradi, Valentina; Swanson, Norman R. - 2005

vanishing parameter estimation error, and extend the integrated conditional moment tests of Bierens (1982, 1990) and Bierens and …

Persistent link: https://www.econbiz.de/10010266361

A predictive comparison of some simple long memory and short memory models of daily US stock returns, with emphasis on business cycle effects

Bhardwaj, Geetesh; Swanson, Norman R. - 2005

This chapter builds on previous work by Bhardwaj and Swanson (2004) who address the notion that many fractional I(d) processes may fall into the empty box" category, as discussed in Granger (1999). However, rather than focusing primarily on linear models, as do Bhardwaj and Swanson, we analyze...

Persistent link: https://www.econbiz.de/10010266365

Predictive density evaluation

Corradi, Valentina; Swanson, Norman R. - 2005

This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and...

Persistent link: https://www.econbiz.de/10010282675