I wonder that what is the mu and sigma formula MLE (maximum likelihood estimates) for a 3 dimension gaussian? It is the same form as 1 and 2 dimension (+ 1 mu and sigma for the new vector)?
2026-03-25 14:28:52.1774448932
Multi-dimensional MLE Gaussian
133 Views Asked by Bumbble Comm https://math.techqa.club/user/bumbble-comm/detail At
1
There are 1 best solutions below
Related Questions in PROBABILITY-DISTRIBUTIONS
- Given is $2$ dimensional random variable $(X,Y)$ with table. Determine the correlation between $X$ and $Y$
- Statistics based on empirical distribution
- Given $U,V \sim R(0,1)$. Determine covariance between $X = UV$ and $V$
- Comparing Exponentials of different rates
- Linear transform of jointly distributed exponential random variables, how to identify domain?
- Closed form of integration
- Given $X$ Poisson, and $f_{Y}(y\mid X = x)$, find $\mathbb{E}[X\mid Y]$
- weak limit similiar to central limit theorem
- Probability question: two doors, select the correct door to win money, find expected earning
- Calculating $\text{Pr}(X_1<X_2)$
Related Questions in NORMAL-DISTRIBUTION
- Expectation involving bivariate standard normal distribution
- How to get a joint distribution from two conditional distributions?
- Identity related to Brownian motion
- What's the distribution of a noncentral chi squared variable plus a constant?
- Show joint cdf is continuous
- Gamma distribution to normal approximation
- How to derive $E(XX^T)$?
- $\{ X_{i} \}_{i=1}^{n} \thicksim iid N(\theta, 1)$. What is distribution of $X_{2} - X_{1}$?
- Lindeberg condition fails, but a CLT still applies
- Estimating a normal distribution
Related Questions in ESTIMATION
- Question on designing a state observer for discrete time system
- Some help with calculating the time remaining please???
- Is the usage of unbiased estimator appropriate?
- How to statistically estimate multiple linear coefficients?
- Is there an intuitive way to see that $\mathbb{E}[X|Y]$ is the least squares estimator of $X$ given $Y$?
- minimizing MSE of estimator $\theta(a,b) = \frac{1}{n} \sum^n_{i=1} Y_ia_i + b$
- a limit about exponential function
- I don't understand where does the $\frac{k-1}{k}$ factor come from, in the probability mass function derived by Bayesian approach.
- hints for calculation of double integral
- estimation of $\mu$ in a Gaussian with set confidence interval
Related Questions in GAUSS-SUMS
- Gauss sum in regular 7-gon
- a special problem about numbers assigned on polygons
- Why did people constructed Quadratic Gauss Sum?
- Gauss sum possible typo
- On a $\mathbb C$-linear map from $M(p-1,\mathbb C)$ to $\mathbb C^\hat G$, where $p$ is an odd prime and $G=\mathbb Z/(p) ^\times$
- $\lim_{n\to\infty}\frac{\sum_{i=1}^ni^{4\lambda}}{\Big(\sum_{i=1}^ni^{2\lambda}\Big)^2}=0$
- Computing number of solutions for equations in $F_{m^s}$ (finite field with $m^s$ elements)
- Jacobi sums Gaussian Sum. Show $J(\rho^{'},\chi^{'}) = (- J(\rho,\chi))^s$
- quadratic gauss sum calculation in sage
- Show that $S^p = \sum\limits_{x \in \Bbb {F_q}^*} \left ( \frac x q \right ) {\omega}^{xp}.$
Trending Questions
- Induction on the number of equations
- How to convince a math teacher of this simple and obvious fact?
- Find $E[XY|Y+Z=1 ]$
- Refuting the Anti-Cantor Cranks
- What are imaginary numbers?
- Determine the adjoint of $\tilde Q(x)$ for $\tilde Q(x)u:=(Qu)(x)$ where $Q:U→L^2(Ω,ℝ^d$ is a Hilbert-Schmidt operator and $U$ is a Hilbert space
- Why does this innovative method of subtraction from a third grader always work?
- How do we know that the number $1$ is not equal to the number $-1$?
- What are the Implications of having VΩ as a model for a theory?
- Defining a Galois Field based on primitive element versus polynomial?
- Can't find the relationship between two columns of numbers. Please Help
- Is computer science a branch of mathematics?
- Is there a bijection of $\mathbb{R}^n$ with itself such that the forward map is connected but the inverse is not?
- Identification of a quadrilateral as a trapezoid, rectangle, or square
- Generator of inertia group in function field extension
Popular # Hahtags
second-order-logic
numerical-methods
puzzle
logic
probability
number-theory
winding-number
real-analysis
integration
calculus
complex-analysis
sequences-and-series
proof-writing
set-theory
functions
homotopy-theory
elementary-number-theory
ordinary-differential-equations
circles
derivatives
game-theory
definite-integrals
elementary-set-theory
limits
multivariable-calculus
geometry
algebraic-number-theory
proof-verification
partial-derivative
algebra-precalculus
Popular Questions
- What is the integral of 1/x?
- How many squares actually ARE in this picture? Is this a trick question with no right answer?
- Is a matrix multiplied with its transpose something special?
- What is the difference between independent and mutually exclusive events?
- Visually stunning math concepts which are easy to explain
- taylor series of $\ln(1+x)$?
- How to tell if a set of vectors spans a space?
- Calculus question taking derivative to find horizontal tangent line
- How to determine if a function is one-to-one?
- Determine if vectors are linearly independent
- What does it mean to have a determinant equal to zero?
- Is this Batman equation for real?
- How to find perpendicular vector to another vector?
- How to find mean and median from histogram
- How many sides does a circle have?
As often happens with MLEs, it's just what you would expect.
The MLE for the matrix of covariances has the sample size $n$ in the denominator and the entries are the sample variances and sample covariances. This matrix has a Wishart distribution with $n-1$ degrees of freedom.
When I first saw the derivation of the MLE of the $3\times3$ or $p\times p$ variance, I was struck by the technique by which it turned out to be useful to view a scalar as the trace of a $1\times 1$ matrix. See this section: http://en.wikipedia.org/wiki/Estimation_of_covariance_matrices#Maximum-likelihood_estimation_for_the_multivariate_normal_distribution