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- Suhr, Ole Bernt, et al.
(författare)
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Amyloid fibril composition within hereditary Val30Met (p. Val50Met) transthyretin amyloidosis families
- 2019
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:2
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The amyloid fibril in hereditary transthyretin (TTR) Val30Met (pVal50Met) amyloid (ATTR Val30Met) amyloidosis is composed of either a mixture of full-length and TTR fragments (Type A) or of only full-length TTR (Type B). The type of amyloid fibril exerts an impact on the phenotype of the disease, and on the outcome of diagnostic procedures and therapy. The aim of the present study was to investigate if the type of amyloid fibril remains the same within ATTR Val30Met amyloidosis families.METHODS: Fifteen families were identified in whom at least two first-degree relatives had their amyloid fibril composition determined. The type of ATTR was determined by Western blot in all but two patients. For these two patients a positive 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy indicated ATTR Type A.RESULTS: In 14 of the 15 families, the same amyloid fibril composition was noted irrespective of differences in age at onset. In the one family, different ATTR fibril types was found in two brothers with similar ages at onset.CONCLUSIONS: Family predisposition appears to have an impact on amyloid fibril composition in members of the family irrespective of their age at onset of disease, but if genetically determined, the gene/genes are likely to be situated at another location than the TTR gene in the genome.
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- Wijayatunga, Priyantha, 1967-
(författare)
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A geometric view on Pearson's correlation coefficient and a generalization of it to non-linear dependencies
- 2016
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Ingår i: Ratio Mathematica. - Italy : eiris. - 1592-7415 .- 2282-8214. ; 30, s. 3-21
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Tidskriftsartikel (refereegranskat)abstract
- Measuring strength or degree of statistical dependence between two random variables is a common problem in many domains. Pearson's correlation coefficient $\rho$ is an accurate measure of linear dependence. We show that $\rho$ is a normalized, Euclidean type distance between joint probability distribution of the two random variables and that when their independence is assumed while keeping their marginal distributions. And the normalizing constant is the geometric mean of two maximal distances; each between the joint probability distribution when the full linear dependence is assumed while preserving respective marginal distribution and that when the independence is assumed. Usage of it is restricted to linear dependence because it is based on Euclidean type distances that are generally not metrics and considered full dependence is linear. Therefore, we argue that if a suitable distance metric is used while considering all possible maximal dependences then it can measure any non-linear dependence. But then, one must define all the full dependences. Hellinger distance that is a metric can be used as the distance measure between probability distributions and obtain a generalization of $\rho$ for the discrete case.
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- Wijayatunga, Priyantha, 1967-, et al.
(författare)
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Appraisal of companies with Bayesian networks
- 2006
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Ingår i: International Journal of Business Intelligence and Data Mining. - : InderScience Publishers. - 1743-8187. ; 1:3, s. 329-346
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Tidskriftsartikel (refereegranskat)abstract
- Appraisal of companies is an important business activity. We mainly apply Bayesian networks for this classification task for Japanese electric company data. Firstly, few standard statistical techniques are performed. Then Bayesian networks are applied in four steps: (1) for implementing a current procedure of economical experts, where economical variables are clustered and then summarised for computing a score for deciding the economical state of the company, (2) the same is done but with clustering of economical variables based on data, (3) the naive Bayes classifier and (4) an improved naive Bayes classifier through adjusting its conditional density of each feature variable given the class variable, which are initially obtained by maximum likelihood estimation. Adjustments are done by using the simulated annealing optimisation. Finally, a sensible way for appraisal of companies is discussed.
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- Wijayatunga, Priyantha, 1967-
(författare)
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Book Review: Bayesian Theory and Applications
- 2013
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Ingår i: Qvintensen. - Stockholm : Svenska statistikfrämjandet. - 2000-1819. ; :4, s. 18-19
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Recension (övrigt vetenskapligt/konstnärligt)
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- Wijayatunga, Priyantha, 1967-
(författare)
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Causal Effect Estimation Methods
- 2014
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Ingår i: Journal of Statistical and Econometric Methods. - : Scienpress Ltd. - 2241-0376. ; 3:2, s. 153-170
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Tidskriftsartikel (refereegranskat)abstract
- Relationship between two popular modeling frameworks of causalinference from observational data, namely, causal graphical model andpotential outcome causal model is discussed. How some popular causaleffect estimators found in applications of the potential outcome causalmodel, such as inverse probability of treatment weighted estimator anddoubly robust estimator can be obtained by using the causal graphicalmodel is shown. We confine to the simple case of binary outcome andtreatment variables with discrete confounders and it is shown how togeneralize results to cases of continuous variables.
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- Wijayatunga, Priyantha, 1967-
(författare)
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Correlation and causation explained
- 2013
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Annan publikation (populärvet., debatt m.m.)abstract
- Though the word correlation means usually how two quantities vary together, perhaps it may be due to extensive use of Pearson’s correlation coefficient. It is often associated with a linear relationship between the two. Even many scientific people misinterpret zero correlation as independence of the two quantities forgetting about what it really means; there is no linear association between the two quantities concerned.Furthermore many confuse correlation with causation, i.e., many interpret non–zero correlation as an implied causal relationship. There are many examples of it even in scientific literature. Here our point is not to discuss all these misinterpretations, but to look at another thing on correlation, that is also related to causation in some sense.
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- Wijayatunga, Priyantha, 1967-
(författare)
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Data Deluge and Its Analysis Issues
- 2016
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Ingår i: Proceedings of the 2nd International Conference in Accounting Researchers and Educators (ICARE 2016). - Kelaniya : Department of Accountancy, University of Kelaniya. ; , s. 21-21
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Konferensbidrag (refereegranskat)abstract
- Current availability of enormous amount of data is mainly due to technological advances. They are useful drawing inferences for creating new businesses, formulation of new policies or revising existing ones, etc. However, much of analyses are performed either by subject domain experts implementing mathematical and computational models incorrectly or by mathematical and computational professionals, purely on data driven basis without paying required attention to the subject domain knowledge. Both of these exercises often result in incorrect inferences and therefore they may harm the society, especially when their inferences are used in practice. We argue that, in order to get valid inferences these two parties should work together. Here we briefly discuss some of the issues that the large-scale data analyses should take into account, especially in open data and big data. We also briefly discuss our solutions that are rather simple to implement.
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