बहुभिन्नरूपी हिंदी उपयोग और उदाहरण

नाम 'ची चुकता' अंततः पीयरसन की आशुलिपि से ग्रीक अक्षर ची के साथ एक बहुभिन्नरूपी सामान्य वितरण में प्रतिपादक के लिए निकला, क्या -½xTΣ-1x के रूप में आधुनिक संकेतन (Σ सहप्रसरण मैट्रिक्स जा रहा है) में प्रकट होता है के लिए -½χ² लेखन।

स्टेटनोट्स: बहुभिन्नरूपी विश्लेषण विषय पर, जी डेविड गारसन द्वारा।

'गतिशील सशर्त सहसंबंध - बहुभिन्नरूपी GARCH मॉडल का एक सरल वर्ग'।

बहुभिन्नरूपी विश्लेषण (Multivariate Analysis)।

""बहुभिन्नरूपी विश्लेषण (Multivariate Analysis)।

बहुभिन्नरूपी आँकड़े (Multivariate statistics)।

बहुभिन्नरूपी इसके अंग्रेजी अर्थ का उदाहरण

While the SA construct has been widely researched, the multivariate nature of SA poses a considerable challenge to its quantification and measurement (for a detailed discussion on SA measurement, see Endsley " Garland, 2000; Fracker, 1991a; 1991b).

Subjective measures also tend to be global in nature, and, as such, do not fully exploit the multivariate nature of SA to provide the detailed diagnostics available with objective measures.

As part of his work on mathematical logic, in connection with Hilbert's tenth problem, Wiens helped find a diophantine formula for the primes: that is, multivariate polynomial with the property that the positive values of this polynomial, over integer arguments, are exactly the prime numbers.

Therefore, univariate EDAs rely only on univariate statistics and multivariate distributions must be factorized as the product of N univariate probability distributions,.

Bivariate and multivariate distributions are usually represented as Probabilistic Graphical Models (graphs), in which edges denote statistical dependencies (or conditional probabilities) and vertices denote variables.

The next stage of EDAs development was the use of multivariate factorizations.

The learning of PGMs encoding multivariate distributions is a computationally expensive task, therefore, it is usual for EDAs to estimate multivariate statistics from bivariate statistics.

The ECGA was one of the first EDA to employ multivariate factorizations, in which high-order dependencies among decision variables can be modeled.

Its approach factorizes the joint probability distribution in the product of multivariate marginal distributions.

Estimation of multivariate normal algorithm (EMNA).

Estimation multivariate normal algorithm with thresheld convergence.

, all the multivariate tests).