Principal component analysisPrincipal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
Three-phase traffic theoryThree-phase traffic theory is a theory of traffic flow developed by Boris Kerner between 1996 and 2002. It focuses mainly on the explanation of the physics of traffic breakdown and resulting congested traffic on highways. Kerner describes three phases of traffic, while the classical theories based on the fundamental diagram of traffic flow have two phases: free flow and congested traffic.
Teletraffic engineeringTeletraffic engineering, telecommunications traffic engineering, or just traffic engineering when in context, is the application of transportation traffic engineering theory to telecommunications. Teletraffic engineers use their knowledge of statistics including queuing theory, the nature of traffic, their practical models, their measurements and simulations to make predictions and to plan telecommunication networks such as a telephone network or the Internet. These tools and knowledge help provide reliable service at lower cost.
Least-squares spectral analysisLeast-squares spectral analysis (LSSA) is a method of estimating a frequency spectrum based on a least-squares fit of sinusoids to data samples, similar to Fourier analysis. Fourier analysis, the most used spectral method in science, generally boosts long-periodic noise in the long and gapped records; LSSA mitigates such problems. Unlike in Fourier analysis, data need not be equally spaced to use LSSA.
Level of measurementLevel of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal, ordinal, interval, and ratio. This framework of distinguishing levels of measurement originated in psychology and has since had a complex history, being adopted and extended in some disciplines and by some scholars, and criticized or rejected by others.
Self-efficacyIn psychology, self-efficacy is an individual's belief in their capacity to act in the ways necessary to reach specific goals. The concept was originally proposed by the psychologist Albert Bandura. Self-efficacy affects every area of human endeavor. By determining the beliefs a person holds regarding their power to affect situations, self-efficacy strongly influences both the power a person actually has to face challenges competently and the choices a person is most likely to make.
Spectral density estimationIn statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the power spectral density) of a signal from a sequence of time samples of the signal. Intuitively speaking, the spectral density characterizes the frequency content of the signal. One purpose of estimating the spectral density is to detect any periodicities in the data, by observing peaks at the frequencies corresponding to these periodicities.
Spectral densityThe power spectrum of a time series describes the distribution of power into frequency components composing that signal. According to Fourier analysis, any physical signal can be decomposed into a number of discrete frequencies, or a spectrum of frequencies over a continuous range. The statistical average of a certain signal or sort of signal (including noise) as analyzed in terms of its frequency content, is called its spectrum.
Self-conceptIn the psychology of self, one's self-concept (also called self-construction, self-identity, self-perspective or self-structure) is a collection of beliefs about oneself. Generally, self-concept embodies the answer to the question "Who am I?". The self-concept is distinguishable from self-awareness, which is the extent to which self-knowledge is defined, consistent, and currently applicable to one's attitudes and dispositions. Self-concept also differs from self-esteem: self-concept is a cognitive or descriptive component of one's self (e.
Self-categorization theorySelf-categorization theory is a theory in social psychology that describes the circumstances under which a person will perceive collections of people (including themselves) as a group, as well as the consequences of perceiving people in group terms. Although the theory is often introduced as an explanation of psychological group formation (which was one of its early goals), it is more accurately thought of as general analysis of the functioning of categorization processes in social perception and interaction that speaks to issues of individual identity as much as group phenomena.
