Questions tagged [modeling]
This tag describes the process of creating a statistical or machine learning model. Always add a more specific tag.
1,012 questions with no upvoted or accepted answers
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GAMM with multiple and crossed random effects
I am new to Generalized additive mixed models (GAMM) and I'm trying to model a behavioral response variable (time spent shading eggs by a nesting bird in minutes ...
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Applying a variance-stabilizing transform to a fitted function (rather than data)
Outline
I'm working with data corrupted by a mixed Poisson-Gaussian noise model (for example with images gathered in astronomy or electron microscopy), and have been using the generalized Anscombe ...
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Reference for the idea that a simpler model can be used when the range of data values is smaller
When we build a statistical-physical model, generally, a simpler model can be justified when the range of data-values is smaller.
I can't be the first person to use this idea, but I also can't find ...
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Pooling samples -- what are the effects
There is an experiment in which biological samples are taken for several treatments and a control. For each treatment, we have enough resources to evaluate 5 samples.
Some researchers suggest (for ...
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Zero values and discontinuity in explanatory variable
One of my independent variables measures worker productivity through the variable $\frac{\log{sales}}{\text{# of workers}}$, and I'm creating one variable for skilled and another for unskilled workers....
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Time series modeling the number of users of a mobile app
I want to model the number of users of an mobile app. This app has two kinds of users: free and paid. I thought of this autoregressive model:
$x_t = Ax_{t-1}$
with $x_t$ being a 4-dimensional vector,...
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Reconstructing joint distribution from marginals
I think this is a rather open question. Suppose I have bi-dimensional data $(x_i, y_i)$. I have some reasonable model for the marginals, say distributions $F_X$ and $F_Y$ (parametric).
How to ...
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How to model time-varying correlation
Suppose I have two time-series variables, $\{x_t\}$ and $\{y_t\}$, where $t\in[1,T]$. I would like to model the correlation $\rho(x_t,y_s)$ as some function of $t$,$s$, and the difference $t-s$. In ...
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Processes behind statistical distribution laws: a compendium?
The simple processes that "explain" the binomial, Gaussian or Poisson distribution are relatively well-known. Johnson or shot noises may be known in restricted area of science. Sometimes, a ...
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Bayesian model selection in PyMC
I'm trying to do model selection using PyMC (v2.2), but having difficulty assessing the models using various Information Criteria and/or Bayes Factor. My model is similar to a typical regression, with ...
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Difficulty with MCMC implementation
I could really use some guided help! I'm having difficulty understanding an MCMC implementation in terms of modeling a data set. I'm working on generating parameters from stellar light curves, and was ...
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How to define and model consumption bundles?
Imagine an a la carte buffet with n different rooms. On entering the buffet you pick a room (let's say American, Mexican or Italian food) where you stay for the duration of your visit.
Once in a room,...
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Creating dummy variables before or after splitting to train/test datasets
I have a data set with a few columns of categorical type. As part of modelling process, I need to convert them into dummy variables. My confusions is whether to do dummy creation before or after ...
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Elo ranking for attack and defence seperately
I want to create a simple statistical model for the bowler versus batsman contest in a game of cricket (it's similar to pitcher versus batter in baseball). Let's say the simple the model is this:
One ...
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Is there any advantage from using Momentum Schedulers in training models using SGD than using a constant momentum of 0.9?
Recently I noticed that some pytorch repos of papers use Learning Rate Scheduler and momentum rate Scheduler , a lot of momentum rate schedulers exist similar to LR scheduler ranging from Lambda, ...
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