Statistical Analysis of Small Sample Fatigue Data

Best Practice Guide on Statistical Analysis of Fatigue Data

Statistical Analysis Methods for the fMRI Data

Functional magnetic resonance imaging (fMRI) is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the fMRI data to be able to find the parts of br...

Domain Adaptation: A Small Sample Statistical Approach

We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample domains, but where we have many samples in each domain. Our goal is to generalize to a new domain. For example, we may want to learn a similarity function using only certain classes of objects, but we desire that this s...

Concepts and Foundations of Data Analysis and Statistical Information in Modern Statistical System

Abstract. One of the most important fundamental principles of official statistics, is the principle of Relevance, Impartiality, and professional ethics. Trust and ensure of the stakeholders and users of official statistics to the professional independency of National Statistical Offices (NSO) and the National Statistical System (NSS), as a social capital, is one of the most important factors fo...

Feature Selection for Small Sample Sets with High Dimensional Data Using Heuristic Hybrid Approach

Feature selection can significantly be decisive when analyzing high dimensional data, especially with a small number of samples. Feature extraction methods do not have decent performance in these conditions. With small sample sets and high dimensional data, exploring a large search space and learning from insufficient samples becomes extremely hard. As a result, neural networks and clustering a...