All Questions
712 questions with no upvoted or accepted answers
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234
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optimize a function in presence of NAs values in R
I would like to maximize the funcToOpt in the code.
Description of the data:
wb and X1 are ...
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0
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518
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How to calculate gradient of partial log-likelihood function in Cox proportional hazards model?
Is there any existing function in R or package that calculates gradient of partial log-likelihood function in Cox proportional hazards model?
I've tried myslef on this question (How to compute ...
- 1,069
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86
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Prior distributions letting a small sample "speak"
I’ve got a general question.
Let k be a parameter which must be estimated. It lies within the interval $[a, b]$, $a$ and $b$ being finite real numbers.
Let us further assume we dispose of a series ...
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326
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how to construct the likelihood if my errors are not Gaussian
My aim is to study the correlation between 2 parameters knowing that I have measurement errors in both parameters, i.e. I have uncertainties on the independent and dependent parameters.
I want to ...
- 460
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92
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Likelihood of a Poisson-described event to occur in the next second
Consider a recurring event for which the time periods between consecutive events is exponentially distributed. For argument's sake, I'm waiting for a taxi on a busy street. How might one calculate the ...
- 400
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184
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0
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119
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Recursive Bayesian Estimation, $p(C_k|\mathbf{x})$ as (discrete) likelihood
I''ve been struggeling with this problem for the last couple of days.
The main goal is to use the probabilistic classification output $p(C_k|\mathbf{x})$, from for example a logistic regression, to ...
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633
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Distribution of a MA(1) process
Suppose I have this MA(1) model:
$y_t = \mu + \epsilon_t + \theta \epsilon_{t-1}$ with $\epsilon_t \sim \mathcal{N}(0,\sigma^2)$
The marginal distribution of $y_t$ for all $t$ is $\mathcal{N}(\...
- 215
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Accounting for minimum dependent measure in data when fitting a distribution
I have what is possible a naive question. I am current comparing various models (i.e. distributions). And the comparisons do not involve different distributions but rather how the model is fed the ...
- 43
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53
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Solving a difficult equation for a variable?
I'm trying to obtain the maximum likelihood estimate of the parameters for a model I'm building. I have constants $\sigma$, $\mu$, and $q_0$; a boolean matrix $\alpha$; and vectors $A, \beta, r, d,$ ...
- 3,132
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92
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Can I split this likelihood term
I have a likelihood that is modelled using the IID distributed noise assumption. Now the likelihood at a 3D location $i$ is normally distributed with 0 mean and some precision $\sigma$. So, I can ...
- 4,730
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Log Likelihoods of Exponential Families
How can one derive the log-likelihood of the saturated model of an exponential family in general?
Differentiating the log likelihood w.r.t $\theta$ gives $y_i=\hat{\mu_i}$ but I don't think replacing ...
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