# likelihood

1. ### Marginalisation of a parameter

Hi everyone, I have a problem with the marginalisation concept. I have a matrix (NxM), where: N refers to the models I tested; M refers to the parameters of each model (i.e., all models have the same M parameters (mass, age, etc., they refer to galaxy properties). Because I have N models I...
2. ### Baye's in distributions

I don't understand theta in the formula for the prior distribution. Isn't the prior (in this case) a normal distribution with some mju and zigma? What does theta mean?
3. ### Demonstrating that MAP -> MLE, Bayes

Note - I can't work out how to write in LaTeX on here, and ascii maths can be quite painful, as a result I have included the LaTeX in this post and provided links where the LaTeX can be read rendered. Also, any answers that make use of R software are fine, I don't have access to anything such...
4. ### Likelihood Function

Can anyone help me understand this? Consider the four observations from de Normal Distribution with variance equal to one y1 < 10, y2 > 10, 5 < y3 < 10 and y4 = 10. The likelihood function is? Would be: Replacing: I want to know if this is correct or have another way of solving this...
5. ### Inference Statistic - Likelihood Function

## LaTeX Code Can anyone help me understand this? Consider the four observations from de Normal Distribution with variance equal to one $y_1 < 10$$, y_2 > 10$, $5 < y_3 < 10$ and $y_4 = 10$. The likelihood function is? Would be: \$ \prod_{1}^{4} \frac{1}{\sqrt(2\pi)}\exp{-\frac{(y_i...
6. ### Interpretation of likelihood ratio and hypothesis testing

Even after extensive search, am unclear on some (basic) concepts regarding likelihood vs. frequentist approach in hypothesis testing. Can you please help? Here we go: Suppose I have observed an outcome O, and I know that a parameter θ has influence on the outcome and can acquire two (and...
7. ### How to calculate the mean of two log-likelihood values.

Hi All, I'm confused how to calculate the mean of two (natural) log-likelihood values. The software I'm using (MrBayes) does this for me automatically... sometimes. But in situations when it does not, I need to calculate it myself. Here is an example: log-likelihood A: -104520.13...
8. ### Calculating likelihood for a particular biological sample. Is is possible?

Hi you all! I've got a problem when trying to analyze some biological data in my PhD. Let's say that I'm interested in performing an analysis using observed values of a random variable (O), whose distribution is unknown, and their expected values (E) using a model like: Ei = k1 * exp ( - k2 ·...
9. ### [HOMEWORK-USING R] Poisson Model using likelihood

Question :A well-known example involving the Poisson model was described by LJ Bortkiewickz (1868-1931). The data refer to the annual number of deaths by horse kicks in battalions of army soldiers. Fourteen battalions were examined over number of years, resulting in a total of 200...
10. ### Likelihood function confusion over definition

When we have a likelihood, say L(theta| x) would we say that L is the likelihood of (x1,x2) or (X1,X2) or neither? Where X1,X2 are the unobserved random variables and x1,x2 the observed values.
11. ### the likehood fonction for Log-periodic-power-law ?

can anyone help me to found the the likehood fonction for Log-periodic-power-law ? log(y(t))=A+(B(t-tc)^beta )(1+Ccos(wlog(tc-t)+phi)) A,B,C,beta,phi,tc,w : are parameters to be estimeted. i can't find an exemple to build analogie with this formula .. i was working with Genetic...
12. ### maximum likelihood

Hello! I would like to know if what I need to do is feasible. Given a sample x=[-1 0 2 3], I would like to know the probability (the likelihood) that the sample has been generated by a normal distribution N(2,2). Thanks a lot, Luis.
13. ### Log-likelihood MLE Markov chain

Hey! I am currently working with Markov chains and calculated the Maximum Likelihood Estimate using transition probabilities as suggested by several sources. I now want to calculate the log-likelihood of the MLE, but I am quite unsure how to do so. Maybe someone can help me out. Thanks...
14. ### [Likelihood of embedded Markov chain] Likelihood of Goldman Yang (GY) rate matrix

This question concerns defining the likelihood of a set of parameters in a rate matrix of an embedded Markov chain. To get a brief idea of the context I will try to explain the problem with a simpler one first. I am working with evolutionary models (see...
15. ### maximum likelihood

good day! below is a bonus question from my previous quiz in probability theory, and i just want to find know the solution for that problem.. please give a complete and detailed solution..thanks and God bless!!
16. ### Using "AIC per sample" to compare logistic regression models

I'm generating nested models using logistic regression and comparing them by AIC. One issue that arises is that not all samples have all independent variables coded. For sake of discussion, let's assume no imputation of missing independent vars: those samples just get dropped when generating...