Structural, loss, and lead time models
Non Gaussian structural time series models
... error loss, the predictive distribution (or operational model) is the optimal estimator of the measurement distribution taken w i t h respect to the density which encapsulates the modus operandi imposed in the ...
249
Long memory and structural breaks in time series models
... In the context of testing for parameter instability, this assumption may be regarded as innocuous since it can be argued th at if a test procedure is capable of detecting small changes in the structure of the model, it ...
223
History-Adjusted Marginal Structural Models: Time-Varying Effect Modification
... over time, despite loss of virologic suppression (Deeks et ...a loss of viral fitness, and as a result, a reduced ability of the virus to deplete CD4 T-cells (Deeks ...Over time, the virus may ...
14
Robust estimation for structural time series models
... A review o f robust filters [ch 2. pgA6] Kitagawa employs a direct method for his filter but a great deal of computation is required . This is especially true when we extend the filter to analyse models with ...
316
Structural Time Series Models for Business Cycle Analysis
... Real time and smoothed esti- mates of the cyclical components. The real time estimates support the view that most of the variation in GDP is permanent, ...real time are never significantly different ...
45
Structural Time Series Models for Business Cycle Analysis
... Real time and smoothed esti- mates of the cyclical components. The real time estimates support the view that most of the variation in GDP is permanent, ...real time are never significantly different ...
45
Three Essays on Structural Stability of Time Series Models
... While the first chapter is based on a single-author paper (see Otto 2019), the latter two chapters are joint works with J¨ org Breitung (see Otto and Breitung 2019) and Nazarii Salish (see Otto and Salish 2019) ...
126
Real Time Detection of Structural Breaks in GARCH Models
... for structural break models with a fixed number of ...be time-consuming and become impractical in real applications where inference needs to be updated ...of models with path dependence such as ...
32
Bayesian inference for nonlinear structural time series models
... September 5, 2012 Abstract This article discusses a partially adapted particle filter for estimating the likelihood of nonlinear structural econometric state space models whose state transition density ...
30
Real Time Detection of Structural Breaks in GARCH Models
... SB-GARCH models with a known fixed number of ...real time estimates, nor is it feasible to estimate SB-GARCH models with an unknown number of states via existing MCMC ...of models are ...of ...
34
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
... of time series [ 29 ...for time series forecasting [ 5 ...proposed loss function can be used for training any direct multi-step deep ...dominant loss function to train and evaluate deep ...
14
On the Equilibrium Without Loss in the Discrete Time Models of Economic Dynamics
... without loss by given # ' , + ' and some ℓ > 0 & ∈ ; and ] ' > 0 - ∈ ; exist only and only when (14) is satisfied; the coefficients ] ∈ ; and equilibrium prices 8 are related by the formula ...
7
Analysis of a cross section of time series using structural time series models
... If the initial differences between the trend and seasonal components in model (1.3) are defined as random with a proper distribution, the estimates of the state [r] ...
247
Semiparametric identification of structural dynamic optimal stopping time models
... interesting structural parameters can be derived from G but also because G is indispensable when, besides identi…cation of the structural parameters, the aim is to predict the conditional choice ...choice ...
25
Temporal Disaggregation Using Multivariate Structural Time Series Models
... In this paper we provide a multivariate framework for temporal disaggregation of time series observed at a certain frequency into higher frequency data. The suggested method uses the seemingly unrelated ...
32
An Empirical Study of Marginal Structural Models for Time-Independent Treatment
... 1 Introduction In observational studies when treatment is not randomly assigned, individual characteristics or an individ- ual’s degree of well-being can affect the health outcome being studied as well as influence ...
15
An Alternative Bayesian Approach to Structural Breaks in Time Series Models
... with structural breaks in time series models, with an explicit focus on the implications for out-of-sample ...a structural break as a permanent change in the value of a parameter of the model ...
49
Structural Time Series Models and the Kalman Filter: a concise review
... a time series structural model each component, such as the trend, cycle or seasonal changes, is explicitly formulated and, therefore, it is possible to get speci…c information about ...a structural ...
30
Testing Structural Change in Time-Series Nonparametric Regression Models
... for structural changes. We focus on testing for structural change in the conditional mean process, and allow for flexibility in other aspects of the time series under both the null and alter- ...
21
Forecasting tourist arrivals using time-varying parameter structural time series models
... With regard to the unobserved components, including the trend, seasonal, cycle and irregular components, it is useful to run BSMs to examine the properties (i.e. stochastic versus deterministic processes) of these ...
22