The parameterization tag has no wiki summary.
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Idea of the Nyblom test?
The nyblom-hansen test gives informations about the stability of the estimated parameters in a model. As far as I understand this test, it looks at the score of the ML at evaluates, how near to zero ...
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Finding a correspondence between time-series elements
My problem deals in particular with time-series data about server performance, but the solution is sure to be applicable to many types of data sets. Pardon me if the answer is well-known; I don't know ...
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Asymptotic property of tuning parameter in penalized regression
I'm currently working on asymptotic properties of penalized regression. I've read a myriad of papers by now, but there is an essential issue that I cannot get my head around.
To keep things simple, ...
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Interpretation of main effect when interaction term being significant (ex. lme)
As an example I use "Pinheiro, J. C. & Bates, D. M. 2000. Mixed-effects models in S and S-PLUS. Springer, New York." page 225, where rats are fed by 3 different diets over time, which body mass ...
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1answer
27 views
Output of hyperbfit?
I want to fit a hyperbolid distribution to my data, in my notation, I have the density
\begin{align*}
H(l;\alpha,\beta,\mu,\delta)&=\frac{\sqrt{\alpha^2-\beta^2}}{2\alpha \delta K_1 ...
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82 views
How do we usually select the best combination of parameters of a machine learning model (for a given dataset)?
Am I wrong, or the standard way of optimizing a machine learning model is by evaluating the algorithm over the (initial) dataset for all possible combinations of parameters, and then pick up the one ...
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How to estimate parameters for a nonlinear model with parameters both inside and outside of trigonometric functions?
For the given set of data $y(t)$ I have a model $y(t) = c_1 cos(\omega t) + c_2 sin(\omega t) + c_3$
How can I estimate parameters $c_1,c_2,c_3$ and $\omega$?
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60 views
Learning the parameter of linear model
I was reading the slides from the following
http://www.slideshare.net/kunegis/searching-microblogs-coping-with-sparsity-and-document-quality
In slide 7, the author proposed just a linear model and ...
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1answer
117 views
Mallow's Cp Question
When comparing each individually generated model's $C_p$ to the number of parameters, which number of parameters is the comparison to? Each individual model or the overall number of parameters?
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1answer
73 views
Proportionality in Bayesian Models: What Is Absorbed?
Considering two Bayesian models:
Poisson Likelihood & Beta Prior:
$p(y|\lambda) \sim \text{Pois}(\lambda)$, $p(\lambda) \sim \text{Be}(a, b)$:
$$ p(\lambda|y) \propto ...
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2answers
261 views
Cross validation and parameter optimization
I have a question about the parameter optimization when I use the 10-fold cross validation.
I want to ask that whether the parameters should fix or not during every fold's model training , i.e. (1) ...
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2answers
329 views
How to use the SD of a normal sampling distribution to specify the gamma prior for the corresponding precision?
The gamma distribution is a commonly used prior distribution for the precision ($1/sd^2$) of a normal distribution in Bayesian hierarchical modeling. I want to use an informed prior for the variance ...
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1answer
90 views
Compound Poisson, preliminary work in R
I need help with following programming code:
Beforehand: I tried to estimate Poisson-parameters, but M.L.E. and M.C. do not give satisfactory results regarding actual to expected, from actuarial ...
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1answer
158 views
Random Forest: what if I know a variable is important
My understanding is the the random forest picks randomly mtry variables to build each decision tree. So if mtry=ncol/3 then each variables will be used on average in 1/3 of the trees. And 2/3 of the ...
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1answer
63 views
Parametrizing the Behrens–Fisher distributions
"On the Behrens–Fisher Problem: A Review" by Seock-Ho Kim and Allen S. Cohen
Journal of Educational and Behavioral Statistics, volume 23, number 4, Winter, 1998, pages 356–377
I'm looking at this ...
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1answer
72 views
Estimating parameters using a different method?
I have a probability distribution which has two parameters $a$ and $b$
I have re-parametrized the distribution such that the new distribution has two parameters $c$ and $d$ where:
$c=a$
but
$d = ...
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1answer
309 views
Re-parameterization of an asymmetric s-shaped function
Is anyone aware of a re-parameterization of any asymmetric s-shaped function (like, but not necessarily the 5 parameter logistic curve), where one of the parameters is the first inflection point of ...
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1answer
67 views
Normalize a periodic parameter
I am using inverse modelling software (PEST) to estimate a periodic parameter for the direction of anisotropy, $\hat{\theta}$, which is somewhere in $[0^{\circ}, 180^{\circ})$ (i.e., has a wavelength ...
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1answer
127 views
Accounting for discrete or binary parameters in Bayesian information criterion
BIC penalizes based on the number of parameters. What if some of the parameters are some sort of binary indicator variables? Do these count as full parameters? But I can combine $m$ binary parameters ...
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1answer
101 views
Gaussian process scale targets
I currently play around with gaussian process regression. I discovered some confusing facts that I like to be answered or maybe has a good mailing list for this at hand:
When I optimize the ...
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1answer
973 views
For which distributions are the parameterizations in BUGS and R different?
I have found some distributions for which BUGS and R have different parameterizations: Normal, log-Normal, and Weibull.
For each of these, I gather that the second parameter used by R needs to be ...
