Results 151 to 160 of about 40,912 (303)

Testing for the footprints of stabilization economic policy in forecast errors. [PDF]

PLoS One
Charemza W, Francq C, Lupu R, Makarova S, Zakoïan JM.   +4 more
europepmc   +1 more source

Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley   +1 more source

Prediction, lag and mixture effects of meteorology and pollutants on the incidence of pulmonary tuberculosis in Jining City, China. [PDF]

BMC Public Health
Cao H, Liu W, Yuan J, Wang W, Hou W.
europepmc   +1 more source

On Testing for Independence Between Generalized Error Models of Several Time Series

Journal of Time Series Analysis, EarlyView.
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi, Bouchra R. Nasri, Bruno N. Rémillard   +2 more
wiley   +1 more source

Pan-European analysis shows stable, low antimicrobial resistance in most bovine and porcine respiratory tract pathogens. [PDF]

Front Microbiol
de Jong A, Temmerman R, Rose M, Simjee S, El Garch F, VetPath Study Group.   +5 more
europepmc   +1 more source

Penalized Convex Estimation in Dynamic Location Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
wiley   +1 more source

Forecasting with a Bivariate Hysteretic Time Series Model Incorporating Asymmetric Volatility and Dynamic Correlations. [PDF]

Entropy (Basel)
Than HT.
europepmc   +1 more source

GARCH MODELI

Ushbu maqolada GARCH modeli va uning tarixi keltirilgan bo’lib, bu model orqali vaqt bo’yicha o’zgaruvchan bo’lgan shartli dispersiya tahlil qilingan.
openaire   +2 more sources

Heteroskedastic Structural Vector Autoregressions Identified via Long‐Run Restrictions

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT A central assumption for identifying structural shocks in vector autoregressive (VAR) models via heteroskedasticity is the time‐invariance of the impact effects of the shocks. It is shown how that assumption can be tested when long‐run restrictions based on the cointegration structure of the variables are available for identifying structural ...
Martin Bruns, Helmut Lütkepohl
wiley   +1 more source

National and regional Temporal trends and forecasting of preterm birth in brazil: evidence from National birth data (2014-2023) with projections to 2030. [PDF]

BMC Pregnancy Childbirth
Victor A, Nhancololo AM, Bah HAF, Xavier SP, Gotine AREM, Moreira VA, Charles CM, Cerqueira-Silva T, Rondó PH.   +8 more
europepmc   +1 more source