Showing 1 - 10 of 114
We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the...
Persistent link: https://www.econbiz.de/10010296732
We analyze multivariate binary time series using a mixed parameterization in terms of the conditional expectations given the past and the pairwise canonical interactions among contemporaneous variables. This allows consistent inference on the influence of past variables even if the...
Persistent link: https://www.econbiz.de/10009219799
Persistent link: https://www.econbiz.de/10001813114
Persistent link: https://www.econbiz.de/10001813634
We develop and test a robust procedure for extracting an underlying signal in form of a time-varying trend from very noisy time series. The application we have in mind is online monitoring data measured in intensive care, where we find periods of relative constancy, slow monotonic trends, level...
Persistent link: https://www.econbiz.de/10010509826
We examine the hypothesis of an increase of humus disintegration by analyzing chemical substances measured in the seepage water of a German forest. Problems arise because of a large percentage of missing observations. We use a regression model with spatial and temporal effects constructed in an...
Persistent link: https://www.econbiz.de/10010477828
Abrupt shifts in the level of a time series represent important information and should be preserved in statistical signal extraction. We investigate rules for detecting level shifts that are resistant to outliers and which work with only a short time delay. The properties of robustified versions...
Persistent link: https://www.econbiz.de/10003581856
Persistent link: https://www.econbiz.de/10008989139
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable...
Persistent link: https://www.econbiz.de/10013135866
Robustified rank tests, applying a robust scale estimator, are investigated for reliable and fast shift detection in time series. The tests show good power for sufficiently large shifts, low false detection rates for Gaussian noise and high robustness against outliers. Wilcoxon scores in...
Persistent link: https://www.econbiz.de/10003482595