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Values greater than 5/9 may indicate a bimodal or multimodal distribution, though corresponding values can also result for heavily skewed unimodal distributions. [28] The maximum value (1.0) is reached only by a Bernoulli distribution with only two distinct values or the sum of two different Dirac delta functions (a bi-delta distribution).
If it has more modes it is "bimodal" (2), "trimodal" (3), etc., or in general, "multimodal". [2] Figure 1 illustrates normal distributions, which are unimodal. Other examples of unimodal distributions include Cauchy distribution, Student's t-distribution, chi-squared distribution and exponential distribution.
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 ...
Such a continuous distribution is called multimodal (as opposed to unimodal). In symmetric unimodal distributions, such as the normal distribution, the mean (if defined), median and mode all coincide. For samples, if it is known that they are drawn from a symmetric unimodal distribution, the sample mean can be used as an estimate of 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.
Besides, when the distribution is unimodal, this interval will include the mode. The smallest credible region (SCR), sometimes also called the highest density region. For a multimodal distribution, this is not necessarily an interval as it can be disconnected. This region will always include the mode.
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]
Multimodal learning, machine learning methods using multiple input modalities; Multimodal transport, a contract for delivery involving the use of multiple modes of goods transport; Multimodality, the use of several modes (media) in a single artifact; Multimodal logic modal logic that has more than one primitive modal operator