- [id] => 206
- [recorddate] => 2010:11:07:14:31:46
- [lastupdate] => 2010:11:07:14:31:46
- [type] => article
- [place] => Cluj-Napoca, Romania
- [subject] => informatics - simulation; mathematics - modeling; mathematics - number theory; mathematics - probability theory; mathematics - statistics
- [relatedworks] =>
- 3 (low):
- 4 (some):
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- Distribution fitting 1. Parameters estimation under assumption of agreement between observation and model, ?id=195
- Agreement between Observation and Theoretical Model: Anderson Darling Statistic, ?id=290
- Maximum Likelihood Estimation in determination of power of the error in bivariate linear models involving generalized Gauss-Laplace distributed variables, ?id=291
- Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data, ?id=302
- Computation of probability associated with Anderson-Darling statistic, ?id=310

- [file] => ?f=206
- [mime] => application/pdf
- [size] => 730921
- [pubname] => Leonardo Electronic Journal of Practices and Technologies
- [pubinfo] => AcademicDirect
- [pubkey] => eISSN 1583-1078
- [workinfo] => 8(15): 81-104
- [year] => 2009
- [title] => Observation vs. observable: maximum likelihood estimations according to the assumption of generalized Gauss and Laplace distributions
- [authors] => Lorentz JÄNTSCHI, Sorana D. BOLBOACĂ
- [abstract] =>

Aim: The paper aims to investigate the use of maximum likelihood estimation to infer measurement types with their distribution shape. Material and Methods: A series of twenty-eight sets of observed data (different properties and activities) were studied. The following analyses were applied in order to meet the aim of the research: precision, normality (Chi-square, Kolmogorov-Smirnov, and Anderson-Darling tests), the presence of outliers (Grubbs’ test), estimation of the population parameters (maximum likelihood estimation under Laplace, Gauss, and Gauss-Laplace distribution assumptions), and analysis of kurtosis (departure of sample kurtosis from the Laplace, Gauss, and Gauss-Laplace population kurtosis). Results: The mean of most investigated sets was likely to be Gauss-Laplace while the standard deviation of most investigated sets of compound was likely to be Gauss. The MLE analysis allowed making assumptions regarding the type of errors in the investigated sets. Conclusions: The proposed procedure proved to be useful in analyzing the shape of the distribution according to measurement type and generated several assumptions regarding their association. - [keywords] => Statistical inference; Accuracy; Observation; Maximum likelihood estimation
- [acknowledgment] => Financial support is gratefully acknowledged to UEFISCSU Romania (ID1051/2007).