Recent content by mtal
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Graduate Quantiles of a log-multivariate-normal-distributed set.
Thanks a lot! I was so concentrated on this whole exp-log idea that I somehow never looked at adding the rows instead of the columns. And thanks for pointing out where I went wrong, you've been tons of help!- mtal
- Post #7
- Forum: Set Theory, Logic, Probability, Statistics
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Graduate Quantiles of a log-multivariate-normal-distributed set.
Yes, I do have the equivalence of a portfolio, in that I'm trying to estimate the behaviour of the price of the set as a whole (i.e. the behaviour of the sum of the prices). What I mean by the "x percentile of N prices" is that I would make some K draws from the multivariate normal...- mtal
- Post #5
- Forum: Set Theory, Logic, Probability, Statistics
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Graduate Quantiles of a log-multivariate-normal-distributed set.
Thanks for the reply! These prices are estimates from a statistical model and are indeed correlated. About the second approach you mentioned: The multivariate log-normal distribution didn't enter my mind before since I had never thought of its existence before. I did some searching and...- mtal
- Post #3
- Forum: Set Theory, Logic, Probability, Statistics
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Graduate Quantiles of a log-multivariate-normal-distributed set.
Hello, Let X be a set of N lognormal prices (in dollars), meaning \log(X) = Y \sim MN(\mu_Y , \Sigma_Y) , i.e. the log of X follows a multivariate normal distribution. Imagine now that one wants to compute various quantiles for this set, e.g. 2.5%, 50% and 97.5\%, and does this by...- mtal
- Thread
- Set
- Replies: 6
- Forum: Set Theory, Logic, Probability, Statistics
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Graduate Confidence intervals for factors+continuous variables
I have y_{ij} = \mu_{i} + \alpha x_{ij} + e_{ij} where i = 1, 2,3 and j = 1, \ldots , r . \mu_{i} represents the mean of the data set plus factor levels i , \alpha x_{ij} is a continuous variable. So, the problem is the following: Construct confidence intervals for \mu_1...- mtal
- Thread
- intervals Variables
- Replies: 1
- Forum: Set Theory, Logic, Probability, Statistics