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A bivariate, multimodal distribution. Figure 4. A non-example: a unimodal distribution, that would become multimodal if conditioned on either x or y. In statistics, a multimodal distribution is a probability distribution with more than one mode (i.e., more than one local peak of the distribution).
In statistics, a unimodal probability distribution or unimodal distribution is a probability distribution which has a single peak. The term "mode" in this context refers to any peak of the distribution, not just to the strict definition of mode which is usual in statistics. If there is a single mode, the distribution function is called "unimodal".
For vehicles, see Dual-mode vehicle. Multimodal transport (also known as combined transport) is the transportation of goods under a single contract, but performed with at least two different modes of transport; the carrier is liable (in a legal sense) for the entire carriage, even though it is performed by several different modes of transport ...
Multisensory integration, also known as multimodal integration, is the study of how information from the different sensory modalities (such as sight, sound, touch, smell, self-motion, and taste) may be integrated by the nervous system. [1] A coherent representation of objects combining modalities enables animals to have meaningful perceptual ...
In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real -valued random variable about its mean. The skewness value can be positive, zero, negative, or undefined. For a unimodal distribution (a distribution with a single peak), negative skew commonly indicates that the tail is on the ...
Multimodal biometric systems use multiple sensors or biometrics to overcome the limitations of unimodal biometric systems. [24] For instance iris recognition systems can be compromised by aging irises [25] and electronic fingerprint recognition can be worsened by worn-out or cut fingerprints. While unimodal biometric systems are limited by the ...
The shape of a distribution will fall somewhere in a continuum where a flat distribution might be considered central and where types of departure from this include: mounded (or unimodal), U-shaped, J-shaped, reverse-J shaped and multi-modal. [1] A bimodal distribution would have two high points rather than one. The shape of a distribution is ...
t. e. In Bayesian statistics, a credible interval is an interval used to characterize a probability distribution. It is defined such that an unobserved parameter value has a particular probability to fall within it. For example, in an experiment that determines the distribution of possible values of the parameter , if the probability that lies ...