The theta model, or Ermentrout–Kopell canonical model, is a biological neuron model originally developed to mathematically describe neurons in the animal...

t {\displaystyle \gamma -\mathrm {Re} _{\theta _{t}}} ) transition model was to develop a transition model based on local variables which could be easily...

prediction model ϵ θ ( x t , t ) {\displaystyle \epsilon _{\theta }(x_{t},t)} , one trains ϵ θ ( x t , σ t ) {\displaystyle \epsilon _{\theta }(x_{t},\sigma...

dispersion model of distributions and includes those families of probability distributions, parameterized by θ {\displaystyle {\boldsymbol {\theta }}} and...

theta model is d θ ( t ) d t = ( I − I 0 ) [ 1 + cos ⁡ ( θ ) ] + [ 1 − cos ⁡ ( θ ) ] {\displaystyle {\frac {d\theta (t)}{dt}}=(I-I_{0})[1+\cos(\theta...

The Hyundai Theta is a gasoline four-cylinder automobile engine family. The third all-aluminum engine of Hyundai Motor Company debuted in the fourth-generation...

F θ : θ ∈ Θ } {\displaystyle {\mathcal {Q}}=\{F_{\theta }:\theta \in \Theta \}} is the set of models considered for inference. The second set P = { F λ...

{\theta |x}})} is also a Gaussian mixture model of the form p ( θ | x ) = ∑ i = 1 K ϕ ~ i N ( μ ~ i , Σ ~ i ) {\displaystyle p({\boldsymbol {\theta |x}})=\sum...

is the following: θ {\displaystyle \theta } has t (time) dependence — the Hull–White model. θ {\displaystyle \theta } and α {\displaystyle \alpha } are...

where the θ 1 , . . . , θ q {\displaystyle \theta _{1},...,\theta _{q}} are the parameters of the model, μ {\displaystyle \mu } is the expectation of...

X_{j})}}={\frac {\lambda _{0}(Y_{i})\theta _{i}}{\sum _{j=i}^{N}\lambda _{0}(Y_{i})\theta _{j}}}={\frac {\theta _{i}}{\sum _{j=i}^{N}\theta _{j}}},} where θj = exp(Xj...

θ λ 0 ( θ t ) {\displaystyle \lambda (t|\theta )=\theta \lambda _{0}(\theta t)} where θ {\displaystyle \theta } denotes the joint effect of covariates...

\partial _{\theta }\log \left(P_{\theta }(x)\right)=\mathbb {E} _{x'\sim P_{\theta }}[\partial _{\theta }E_{\theta }(x')]-\partial _{\theta }E_{\theta }(x)\...

{\displaystyle \{P_{\theta }:\theta \in \Theta \}} indexed by a parameter θ {\displaystyle \theta } . A parametric model is a model in which the indexing...

_{-\pi }^{\pi }d\theta _{1}\cdots d\theta _{L}\;e^{\beta J\cos(\theta _{1}-\theta _{2})}\cdots e^{\beta J\cos(\theta _{L-1}-\theta _{L})}\\&=2\pi \prod...

\theta _{j}} , given the occurrence of event y, we must begin with a model providing a joint probability distribution for θ j {\displaystyle \theta _{j}}...

function p ( x ∣ θ ) {\displaystyle p(x\mid \theta )} , the posterior distribution p ( θ ∣ x ) {\displaystyle p(\theta \mid x)} is in the same probability distribution...

model of order q: X t = μ + ε t + θ 1 ε t − 1 + ⋯ + θ q ε t − q = μ + ∑ i = 1 q θ i ε t − i + ε t , {\displaystyle X_{t}=\mu +\varepsilon _{t}+\theta...

the model has the following governing equations: d θ i d t = ω i + 1 N ∑ j = 1 N K i j sin ⁡ ( θ j − θ i ) , i = 1 … N {\displaystyle {\frac {d\theta _{i}}{dt}}=\omega...

{\displaystyle S_{\text{conf}}/k_{\rm {B}}\approx -\theta _{A}\ln(\theta _{A})-(1-\theta _{A})\ln(1-\theta _{A}).} On the other hand, the entropy of a molecule...

;\theta )=\prod _{k=1}^{n}\,f_{k}^{\mathsf {univar}}(x_{k};\theta )~.} The goal of maximum likelihood estimation is to find the values of the model parameters...

Theta (UK: /ˈθiːtə/ , US: /ˈθeɪtə/) uppercase Θ or ϴ; lowercase θ or ϑ; Ancient Greek: θῆτα thē̂ta [tʰɛ̂ːta]; Modern: θήτα thī́ta [ˈθita]) is the eighth...

Autowave Biological neuron model Computational neuroscience Hodgkin–Huxley model Morris–Lecar model Reaction–diffusion Theta model Chialvo map Sherwood, William...

equation Goldman equation Memristor Neural accommodation Reaction–diffusion Theta model Rulkov map Chialvo map Hodgkin AL, Huxley AF (August 1952). "A quantitative...

_{i}} are the parameters of the autoregressive part of the model, the θ i {\displaystyle \theta _{i}} are the parameters of the moving average part and the...

{\displaystyle \{p_{\theta }\}_{\theta \in \Theta }} of distributions, then solve for min θ L ( p θ , p ∗ ) {\displaystyle \min _{\theta }L(p_{\theta },p^{*})} for...

u_{1},\dots ,u_{d}\ ;\ \theta \ )=\psi ^{-1}\!{\bigl (}\ \psi (u_{1};\theta )\ +\ \cdots \ +\ \psi (u_{d};\theta )\ ;\ \theta \ {\bigr )}} where   ψ :...

f(x;\alpha ,\theta )={\frac {x^{\alpha -1}e^{-x/\theta }}{\theta ^{\alpha }\Gamma (\alpha )}}\quad {\text{ for }}x>0{\text{ and }}\alpha ,\theta >0.} Here...

Rendleman–Bartter model (1980) or Dothan model (1978) explains the short rate as d r t = θ r t d t + σ r t d W t {\displaystyle dr_{t}=\theta r_{t}\,dt+\sigma...

p(\theta ,\varphi \mid x)\propto p(x\mid \theta )p(\theta \mid \varphi )p(\varphi ).} This is the simplest example of a hierarchical Bayes model. The...