Results 121 to 130 of about 15,261 (244)

Gaussian semiparametric estimation of multivariate fractionally integrated processes [PDF]

This paper analyzes the semiparametric estimation of multivariate long-range dependent processes. The class of spectral densities considered includes multivariate fractionally integrated processes, which are not covered by the existing literature.
Katsumi Shimotsu
core  

Modelling and forecasting liquidity supply using semiparametric factor dynamics [PDF]

, 2009
We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically.
Hautsch, Nikolaus, Andrija Mihoci, Wolfgang Karl Härdle, Härdle, Wolfgang Karl, Mihoci, Andrija, Nikolaus Hautsch, Härdle, Wolfgang   +6 more
core   +1 more source

Doubly Robust Estimation and Semiparametric Efficiency in Generalized Partially Linear Models with Missing Outcomes

Stats
We investigate a semiparametric generalized partially linear regression model that accommodates missing outcomes, with some covariates modeled parametrically and others nonparametrically. We propose a class of augmented inverse probability weighted (AIPW)
Lu Wang, Zhongzhe Ouyang, Xihong Lin
doaj   +1 more source

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

Journal of Forecasting, Volume 45, Issue 4, Page 1985-2000, July 2026.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch, Candace Berrett, Mason Ferlic, Kimberly F. Sellers   +3 more
wiley   +1 more source

Robustness of a semiparametric estimator of a copula [PDF]

Copulas offer a convenient way of modelling multivariate observations and capturing the intrinsic dependence between the components of a multivariate random variable.
Param Silvapulle, Mervyn J. Silvapulle, Gunky Kim   +2 more
core  

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta‐Diversity

Statistics in Medicine, Volume 45, Issue 15-17, July 2026.
ABSTRACT The human microbiome plays a crucial role in health, but understanding its dynamic relationship with the host requires regular monitoring. Beyond challenges such as high dimensionality and sparsity, additional complexities arise, particularly within‐cluster correlation from repeated measures and pervasive missing data. To address these issues,
Jinyuan Liu, Ke Xu, Jane F. Ferguson, Kaidi Kang, Yue Wang, Yuqi Qiu, Lucy Shao, Shengjia Tu, Tanya T. Nguyen, Tuo Lin, Xinlian Zhang   +10 more
wiley   +1 more source

ESTIMASI MODEL REGRESI SEMIPARAMETRIK MENGGUNAKAN ESTIMATOR KERNEL UNIFORM (Studi Kasus: Pasien DBD di RS Puri Raharja)

E-Jurnal Matematika, 2015
Semiparametric regression model approach is a model approach that combines parametric regression models and nonparametric regression. On semiparametric regression, most explanatory variables are parametric and nonparametric others are.
ANNA FITRIANI, I GUSTI AYU MADE SRINADI, MADE SUSILAWATI   +2 more
doaj  

Hiring at the tip of the funnel: Externalizing the work of integrating and coordinating diverse human capital

Strategic Management Journal, Volume 47, Issue 7, Page 1935-1979, July 2026.
Abstract Research Summary We adopt a network‐based perspective to examine the effects of hiring strategies in terms of the diversity of hiring sources. Considering the transferability of general and firm‐specific skills, we propose that firms can reduce integration costs while gaining diversity benefits when they hire from a focused set of firms that ...
Sang Won Han, Shinjae Won
wiley   +1 more source

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal of Economic Surveys, Volume 40, Issue 3, Page 1672-1686, July 2026.
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

On Exponential‐Family INGARCH Models

Journal of Time Series Analysis, Volume 47, Issue 4, Page 912-918, July 2026.
ABSTRACT A range of integer‐valued generalised autoregressive conditional heteroscedastic (INGARCH) models have been proposed in the literature, including those based on conditional Poisson, negative binomial and Conway‐Maxwell‐Poisson distributions. This note considers a larger class of exponential‐family INGARCH models, showing that maximum empirical
Alan Huang, Thomas Fung, Kyle Macaskill, Rowan Aukes   +3 more
wiley   +1 more source