Tracking an Auto-Regressive Process with Limited Communication per Unit Time [PDF]
Entropy, 2021 Samples from a high-dimensional first-order auto-regressive process generated by an independently and identically distributed random innovation sequence are observed by a sender which can communicate only finitely many bits per unit time to a receiver ...
Rooji Jinan +2 more
doaj +8 more sources
Varying-Coefficient Additive Models with Density Responses and Functional Auto-Regressive Error Process [PDF]
EntropyIn many practical applications, data collected over time often exhibit autocorrelation, which, if unaccounted for, can lead to biased or misleading statistical inferences. To address this issue, we propose a varying-coefficient additive model for density-
Zixuan Han +3 more
doaj +6 more sources
Auto-regressive independent process analysis without combinatorial efforts [PDF]
Pattern Analysis and Applications, 2009 We treat the problem of searching for hidden multi-dimensional independent auto-regressive processes (auto-regressive independent process analysis, AR-IPA). Independent subspace analysis (ISA) can be used to solve the AR-IPA task. The so-called separation theorem simplifies the ISA task considerably: the theorem enables one to reduce the task to one ...
András Lőrincz, , Barnabas Poczos
exaly +2 more sources
Journal of Algorithms & Computational Technology, 2019 Current algorithms for estimating auto-regressive moving average parameters of transistor 1/f process are usually under noiseless background. Transistor noises are measured by a non-destructive cross-spectrum measurement technique, with transistor noise ...
Chen Wang +5 more
doaj +2 more sources
Appropriateness of correlated first-order auto-regressive processes for modeling daily temperature records [PDF]
Physica A: Statistical Mechanics and Its Applications, 2006 Accepted for publication in Physica ...
Radhakrishnan Nagarajan
exaly +3 more sources
A Generalized Estimating Equations Approach for Modeling Spatially Clustered Data
Austrian Journal of Statistics, 2021 Clustering in spatial data is very common phenomena in various fields such as disease mapping, ecology, environmental science and so on. Analysis of spatially clustered data should be different from conventional analysis of spatial data because of the ...
Nasrin Lipi +2 more
doaj +1 more source
Shaping energy cost management in process industries through clustering and soft sensors
Frontiers in Energy Research, 2023 With the ever-increasing growth of energy demand and costs, process monitoring of operational costs is of great importance for process industries.
Yu Lu +8 more
doaj +1 more source
Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes [PDF]
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005 We present a framework for the classification of visual processes that are best modeled with spatio-temporal autoregressive models. The new framework combines the modeling power of a family of models known as dynamic textures and the generalization guarantees, for classification, of the support vector machine classifier. This combination is achieved by
Antoni B. Chan, Nuno Vasconcelos
openaire +1 more source
Maximum Likelihood and Modified Maximum Likelihood Estimates of Linear Models with Errors Following Auto Regressive Process [PDF]
The Egyptian Statistical Journal, 1989 The estimation of parameters of linear models with errors following first order auto-regressive process has been investigated. The Modified Maximum likelihood estimates, introduced by Patterson and Thompson (1971,1974) have been derived.
Heba El-Laithy
doaj +1 more source
A novel machine learning approach to analyzing geospatial vessel patterns using AIS data
GIScience & Remote Sensing, 2022 In the maritime environment, the Automatic Identification System (AIS) contains information related to vessel trajectories that can be used to detect unusual maritime occurrences and maritime traffic patterns.
Martha Dais Ferreira +2 more
doaj +1 more source