| 1. |
- Holst, Ulla, et al.
(författare)
-
Recursive estimation in switching autoregressions with Markov regime
- 1994
-
Ingår i: Journal of Time Series Analysis. - : Wiley. - 0143-9782 .- 1467-9892. ; 15:5, s. 489-506
-
Tidskriftsartikel (refereegranskat)abstract
- A hidden Markov regime is a Markov process that governs the time or space dependent distributions of an observed stochastic process. We propose a recursive algorithm for parameter estimation in a switching autoregressive process governed by a hidden Markov chain. A common approach to the recursive estimation problem is to base the estimation on suboptimal modifications of Kalman filtering techniques. The main idea in this paper is to use the maximum likelihood method and from this develop a recursive EM algorithm.
|
|
| 2. |
|
|
| 3. |
- Lindström, Johan, et al.
(författare)
-
Background and Foreground Modeling Using an Online EM Algorithm
- 2006
-
Ingår i: IEEE International Workshop on Visual Surveillance. ; VS2006, s. 9-16
-
Konferensbidrag (refereegranskat)abstract
- A novel approach to background/foreground segmentation using an online EM algorithm is presented. The method models each layer as a Gaussian mixture, with local, per pixel, parameters for the background layer and global parameters for the foreground layer, utilising information from the entire scene when estimating the foreground. Additionally, the online EM algorithm uses a progressive learning rate where the relative update speed of each Gaussian component depends on how often the component has been observed. It is shown that the progressive learning rate follows naturally from introduction of a forgetting factor in the log-likelihood. To reduce the number of mixture components similar foreground components are merged using a method based on the Kullback-Leibler distance. A bias is introduced in the variance estimates to avoid the known problem of singularities in the log-likelihood of Gaussian mixtures when the variance tends to zero. To allow a decoupling of the learning rate of the Gaussian components and the speed at which stationary objects are incorporated into the background a CUSUM detector is used instead of the prevailing method that uses the ratio of prior probability to standard deviation. The algorithm is scale invariant and its properties on gray-scale and RGB videos, as well as on output from an edge detector, is compared to that of another algorithm. Especially for the edge detector video performance increases dramatically.
|
|
| 4. |
- Lindström, Johan, et al.
(författare)
-
Influence of solar zenith angles on observed trends in the NOAA/NASA 8-km Pathfinder normalized difference vegetation index over the African Sahel
- 2006
-
Ingår i: International Journal of Remote Sensing. - : Informa UK Limited. - 1366-5901 .- 0143-1161. ; 27:9-10, s. 1973-1991
-
Tidskriftsartikel (refereegranskat)abstract
- The strong systematic change in solar zenith angles (SZA) due to annual orbital drift of the NOAA satellites has raised the suspicion of the influence of residual illumination on the calibrated normalized difference vegetation index (NDVI) derived from the Pathfinder AVHRR Land (PAL) database. The aim of this work is to analyse if trends in AVHRR NDVI from 1982 to 2000 over the Sahel region in Africa depend on variations in SZA. The analysis uses both ordinary least squares regression and cointegration to analyse possible linear dependencies between NDVI and SZA on a per satellite basis. Tests for integration and cointegration fail to find any significant evidence for either. This, together with the ability of simple deterministic models to explain primarily SZA constitutes evidence against integration and cointegration, indicating that linear relationships can be examined using ordinary linear regression. Regression gives no consistent relationship between NDVI and SZA and the explanatory power (R 2) of the regression is low (on average 0.08). However there is some evidence for downward bias in NDVI due to nonlinear interactions between NDVI and SZA when SZA is large (>= 80 degrees) leading to the conclusion that PAL data from the year 2000 should not be used for analyses in these environments.
|
|
| 5. |
|
|
| 6. |
- Malmberg, Anders, et al.
(författare)
-
A real-time assimilation algorithm applied to near-surface ocean wind fields
- 2008
-
Ingår i: Environmetrics. - : Wiley. - 1099-095X .- 1180-4009. ; 19:3, s. 319-330
-
Tidskriftsartikel (refereegranskat)abstract
- Abstract in UndeterminedMarine operations depend on the ability to forecast suddenly appearing storms, and failures often cause great damage. As part of a sea-state alarm study, meteorological forecasts overlaid with satellite observations sent to ships have been found to be a useful too]. In this paper we present a real-time assimilation algorithm that extends this tool using statistical methods. The algorithm is applied to near-surface ocean wind fields. A Kalman filter based on a spatio-temporal state-space model provides a basis for emulation of the atmospheric model. The main contribution of this paper is the algorithm that makes it possible to use the information in the satellite observations over the full spatial domain of interest at a real-time basis.
|
|
| 7. |
- Malmberg, Anders, et al.
(författare)
-
Forecasting near-surface ocean winds with Kalman filter techniques
- 2005
-
Ingår i: Ocean Engineering. - : Elsevier BV. - 1873-5258 .- 0029-8018. ; 32:3-4, s. 273-291
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper a statistical forecasting model designed for bounded areas of near-surface ocean wind speeds is implemented. Dimension reduction is achieved by decomposing the covariance structure into one large-scale and one small-scale component using empirical orthogonal functions. The large-scale component is modelled with an AR process and forecasts are calculated by applying a Kalman filter. The model is suited for stable weather situations as for unsteady situations it requires more frequent wind information. From the prediction variance fields it is possible to identify where unexpected weather usually enters the area.
|
|
| 8. |
|
|
| 9. |
- Åberg, Sofia, et al.
(författare)
-
An image warping approach to spatio-temporal modelling
- 2005
-
Ingår i: Environmetrics. - : Wiley. - 1099-095X .- 1180-4009. ; 16:8, s. 833-848
-
Tidskriftsartikel (refereegranskat)abstract
- In this article we present a spatio-temporal dynamic model that can be realized using image warping. Image warping is a non-linear deformation which maps every point in one image plane to a point in another image plane. Using thin-plate splines, these deformations are defined by how a small set of points is mapped, making the method computationally tractable. In our case the dynamics of the process is modelled by thin-plate spline deformations and how they vary in time. Thus we make no assumption of stationarity in time. Finding the deformation between two images in the space-time series is a trade-off between a good match of the images and, a smooth, physically plausible, deformation. This is formulated as a penalized likelihood problem, where the likelihood measures how good the match is and the penalty comes from a prior model on the deformation. The dynamic model we suggest can be used to make forecasts and also to estimate the uncertainties associated with these. An introduction to image warping and thin-plate splines is given as well as an application where the methodology is applied to the problem of nowcasting radar precipitation.
|
|
| 10. |
- Baldetorp, Bo, et al.
(författare)
-
Statistical evaluation of cell kinetic data from DNA flow cytometry (FCM) by the EM algorithm
- 1989
-
Ingår i: Cytometry. - : Wiley. - 0196-4763 .- 1097-0320. ; 10:6, s. 695-705
-
Tidskriftsartikel (refereegranskat)abstract
- Flow cytometric DNA measurements yield the amount of DNA for each of a large number of cells. A DNA histogram normally consists of a mixture of one or more constellations of G0/G1-, S-, G2/M-phase cells, together with internal standards, debris, background noise, and one or more populations of clumped cells. We have modelled typical DNA histograms as a mixed distribution with Gaussian densities for the G0/G1 and G2/M phases, an S-phase density, assumed to be uniform between the G0/G1 and G2/M peaks, observed with a Gaussian error, and with Gaussian densities for standards of chicken and trout red blood cells. The debris is modelled as a truncated exponential distribution, and we also have included a uniform background noise distribution over the whole observation interval. We have explored a new approach for maximum-likelihood analyses of complex DNA histograms by the application of the EM algorithm. This algorithm was used for four observed DNA histograms of varying complexity. Our results show that the algorithm works very well, and it converges to reasonable values for all parameters. In simulations from the estimated models, we have investigated bias, variance, and correlations of the estimates.
|
|
