The aim of this paper is to discuss several aspects of the MIG distribution useful for modelling positive data. We specifically discuss transformations, the derivation of moments, fitting of models, and a shape analysis of the transformations. Finally, real examples from engineering, environment, ...
The GEG distribution enables shifting the attention from traditional means and standard deviations to the entire RT distribution. The mathematical properties of the GEG distribution are presented and investigated via simulations. Additionally, the GEG distribution is featured via four real-life data sets....
Real-Life Examples of Gaussian mixture models Here are a few instances of practical applications for GMMs: Clustering: GMMs can be used to spot trends and put related observations in one group. A GMM could be used, for instance, to group clients into various segments based on their purchasing...
Gaussian distribution; reconstructed basic probability assignment; Dempster-Shafer evidence theory; multi-source information fusion; belief entropy1. Introduction Multi-source information fusion refers to the processing and fusion of data collected from diverse knowledge sources or sensors. It is now used ...
distribution of Gaussian blobs, resulting in clearer differentiation between objects and their background (see Fig. 1). To address the challenge (ii), we propose a Box-Focused Sampling strategy using 2D boxes to generate object probability distribution in 3D spaces, allowing effective probabilistic ...
Examples Attach packages library(cvms) library(groupdata2) # fold() partition() library(knitr) # kable() library(dplyr) # %>% arrange() Load data The dataset participant.scores comes with cvms: data <- participant.scores Fold data Create a grouping factor for subsetting of folds using ...
Fig. 2.2. Examples of channel models. • Binary symmetric channel: Both the input and output are binary with alphabet {0, 1}. The input is swapped at the output with probability 1 − p. Such a model can be used to describe the errors in demodulation and decoding, where 1 − p ...
GaussianUnitaryMatrixDistribution[\[Sigma], n] represents a Gaussian unitary matrix distribution with matrix dimensions {n, n} and scale parameter \[Sigma]. GaussianUnitaryMatrixDistribution[n] represents a Gaussian unitary matrix distribution with unit
This results in an increased spread of data, especially for lower SNR values, like what was observed for some HRV measures for ectopic noise. These measures do not conform well to straight line fitting despite having a highly significant p-value as displayed in Fig. 8. Figure 8 Examples of...
Examples include discontinuous values, bullets, tables where classification can be checked given specific targets, or signal temporal logic (STL) [18]. The bounded uncertain parameter space Δ is classified as safe or unsafe depending on whether all the constraint functions in Eq. (2) are ...