In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class specific pattern variation based on tangent distance within a statistical framework for classification. The model is an effective means to explicitly incorporate invariance with respect to transformations that do not change...

Conventional mammography is considered the modality of choice for the detection of breast cancer. The process involves a human radiologist visually diagnosing the mammogram, which causes limitations such as missing a cancer and/or diagnosing a false cancer. Another disadvantage of conventional mammography is the variability among screening radiologists in interpreting mammographic images. The o...

Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P

Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P

A statistical analysis of the nucleotide sequence variability in 14 published hepatitis B virus (HBV) genomes was carried out using parametric and nonparametric methods. A parametric statistical model revealed that the different regions of the genome differed significantly in their variability. The conclusion was supported by a nonparametric kernel-density model of the HBV genome. Genes S, C, a...

Reasoning about overall variability in a data set, and the partitioning of variability into explained and unexplained, is a key aspect of statistical reasoning. It also provides a powerful conceptual framework for unifying several sometimes disparate topics of introductory statistics such as linear regression, ANOVA, and significance testing of a fitted model. This type of reasoning creates a p...

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control ...

Understanding variability of population abundances is of central concern to theoretical and applied evolutionary ecology, yet quantifying the conceptually simple idea has been substantially problematic. Standard statistical measures of variability are particularly biassed by rare events, zero counts and other ‘non-Gaussian’ behaviour, which are often inappropriately weighted or excluded from an...

the main purpose of this article is, showing similar fluctuation of temperature series and their consistency with what happened in the global level. in addition, it determines new estimates of regional seasonal and annual temperature trends over iran, after the detection of artificial and natural non homogenous points of 33 synoptic stations for the period of 1960 2010. the 22 stations with sho...

[1] We describe the upscaled groundwater flow and solute transport characteristics of two-dimensional hydraulic conductivity fields with three fundamentally different spatial textures and consider the conditions under which physical mobile–immobile domain mass transfer occurs in these fields. All three fields have near-identical lognormal univariate conductivity distributions, as well as near-i...