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Questions tagged [fitting]

The process of fiting some statistical model to a particular set of data. Mostly done on a computer, and using varied numerical methods such as optimization or numerical integration, or simulation.

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What does the error of the neural network model mean? [on hold]

I m fiting a neural network model using R and with the library(neuralnet) but i found the error of the neural network model 500.222 that is not logical at all .. I got this Error when i wrote this ...
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R - how to estimate shape and scale parameters of Weibull distribution for claims development factors

I have a set of insurance data. Development factors fall with period, so follow Weibull distribution. I want to estimate Weibull parameters and smooth Development Factors. If I estimate parameters of ...
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Fitting wrong copula type to a real data set

I have developed a new mixture copula model. This model overcomes some limitation of copula models. I tested my new model on a simulation data. The model shows a superior result. My supervisor asked ...
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Inferring GMM parameters with Gibbs Sampling

On my book, "Machine Learning A Probabilistic Approach". It's stated that is straightforward to derive a Gibbs sampling algorithm to fit a mixture model, especially if we use conjugate priors. So ...
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How do I fit a cumulative Gaussian distribution in R? [closed]

I am trying to fit a cumulative Gaussian distribution function to my data, but I'm not sure how to do this. From what I understand, the fitting process tries to find the mean and standard deviation of ...
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Model fit for StMoMo

As a statistics newbie, I am trying to model mortality. I grabbed majority of the code from the package Vignette, and fitted the data. However, model fit does not seem to be great in my reproducible ...
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43 views

Compute log-likelihood from sum of squares?

I have fit a 2D Gaussian to a surface in Matlab and need to compute the log-likelihood of this fit. Can One use the sum of squares between the Gaussian model and the actual surface to compute the log-...
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AR(1)-GARCH(1,1). A bad fit with log likelihood?

Consider these two DCC models: ...
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3answers
123 views

Fit data to parametric distribution

I have data with nice bell-shaped histogram PDF. However, the Normal distribution fitting (by calculating mean and variance) does not work as the figure below. My question is that if there are other ...
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Best way to model the dependency of these two random variables (copula?)

I'm modelling the joint PDF of two variables that looks like this , where vt and vr are the random variables. The dashed line shows the joint pdf assuming they are independent (the product of its ...
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1answer
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Choosing model for feature selection on categorial data

I have a dataset composed 30 features and 1 response. My response is 0 or 1 and, all of my features composed three status includes = -1,0,1. I wanted to do features selections in R, firstly I want to ...
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2answers
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How can I do a fit for negative $y$-data, which has exponential phenomena? [closed]

How can I do a fit for negative $y$-data, which has exponential phenomena? Such as: ...
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24 views

Proof that sequential GARCH fitting is not efficient?

I've read that authors like Tsay (as well as several other researchers) use a sequential method for fitting a ARCH-type model. This means first estimating the conditional mean model (ARMA-type) and ...
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Data Transformation to achieve Linearity

One assumption of OLS regression is Linearity. To check whether the assumption holds, you can plot component + residual plots or partial residual plots. When a linear relationship is apparent, is's ...
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43 views

Fitting a multiple linear regression in R [closed]

I have annual mean temperature and precipitation data from 1901 to 2015: I want to do a multiple linear regression: ...
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33 views

Estimating posterior probability from a random grid

I am simulating the evolution of galaxies, and want to find the distributions of input parameters that best reproduce an observation of a particular galaxy. I have a measurement $y \pm \sigma$ of a ...
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r - Poor model fit with StMoMo package on Human Mortality Database

I am fitting USA mortality data from Human Mortality Database (with data downloaded from here after registering for a free account https://www.mortality.org/cgi-bin/hmd/hmd_download.php) with the ...
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Measure goodness of fit between a model that has error and data with error

Is there a way to express how well a model matches data where both have uncertainties? I looked for other examples that may capture this, but was unsuccessful in finding one. If you happen to know of ...
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How to detect an increase in a loess model fitted value at the end

Sorry if the question is trivial, but I'm not finding a proper idea for this issue. I'd like to find if a series of fitted value of a loess is increasing in the end. I'm working with some data like ...
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Fitting power law with loglog or exponential? [duplicate]

I have $x$- and $y$-data, and I want a power-law fit ($y=ax^b$). I always fit $\log(x)$ and $\log(y)$ by $p_1x+p_2$ (Matlab poly1), but when I fit $x$ and $y$ with $...
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1answer
29 views

$2D$ Maximum Likelihood Fit

I have read a couple of places that it is possible to do a $2D$ (or $3D$) maximum likelihood fit, but I can't seem to understand how this would work. Suppose I'm considering a probability distribution ...
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24 views

Compairing the fit of quasi-Poisson and negative binomial models

Is there any way to compare the fit of quasi-Poission and negative binomial models in R?
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58 views

Using full covariance matrix of a linear fit reduces the errors?

I am currently studying linear fitting and error propagation. The model to fit is this: $$B ( N , Z ) = a _ { v } A - a _ { s } A ^ { 2 / 3 } - a _ { c } \frac { Z ( Z - 1 ) } { A ^ { 1 / 3 } } - a ...
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How to understand the results of nonlinear mixed-effects regression model

I have some data, obtained from 4 different groups. Each repeat is some 4 parametric sigmoid. I need to fit the data to sigmoidal function and answer the question, whether sigmoids are different ...
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How to solve systems of linear equations with random variables? How to identify model parameters?

I want to learn know how to solve systems of linear equations with randomness. Example of a deterministic version of the sort of problem I want to solve: ...
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119 views

Bayesian networks with continuous variables in Python [closed]

I am trying to create a Bayesian network model (Probabilistic graphical model) in Python, that can handle continuous data. I have tried using pgmpy, but the 'fit' function in pgmpy has not yet been ...
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Correct Interpretation of copula contour plots

Going into exploratory data analysis with the intention of fitting copula models, I was looking at the famous copula and they mention here that either contour or 3D ...
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46 views

How to fit a distribution to binned values that come from administrative data?

Fitting a distribution to data (e.g. with maximum likelihood), or testing goodness of fit (e.g. with Kolmogorov-Smirnov) assumes that the data are randomly drawn from a population. But what if the ...
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fitting for random remnants of known perturbers

I have the following problem: We try to analysis spectra. In our data analysis, we have to correct for perturbers that occur always at the same frequency and can be approximated by a Gaussian of ...
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1answer
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How do I best use a fit statistic like chi-squared fit for a model that predicts two independent sets of measurements?

I have a model $M(\vec{x})$ for a vector of model parameters $\vec{x}$ that predicts two sets of measurements that I have taken - $v(h)$ and $L(h)$. The two independent data sets each have their own ...
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2answers
76 views

Best estimation of a fitting parameter to measured data

My goal is to estimate a parameter $\alpha_1 = (\alpha_{11}, \alpha_{12})$ which provides the best fit of certain measured data (a readout of some currents in a set of positions for a set of loads) to ...
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1answer
33 views

Are there theoretical reasons for choosing between similar distributions?

I'm interested in estimating the distributions of a few skewed datasets, for example extreme heat, and extreme rainfall. There are many distributions that can be fit to these kinds of data, for ...
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2answers
59 views

How to fit laplace/exponential distribution to cosine similarities?

I am a computational biologist with little experience fitting data. I'm trying to fit a distribution of cosine similarities computed between sparse matrices. The goal is to be able use this ...
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Can I use this distribution to model my data according to these plots?

I used the Anderson-Darling and the KS tests to decide whether my data and the distribution fitted on my data has the same distribution. Both tests rejects the null hypothesis. However when I look at ...
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1answer
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Why random numbers from fitted distribution do not have the same distribution as the sample data?

I have a data set and I would like to fit a t distribution on it. I use R or Python to feed into my data, and I get the degrees of freedom, the location and the scale parameters. After that, I ...
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26 views

How to get specific terms of a polynomial function in a regression?

I want to simplify data from a complex modell like: fit <- lm(z ~ poly(a,4)*poly(b,5)*poly(c,6), data = somewhat) As I don't know which terms of the complete ...
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Average of two fits vs fit of a combined data

Lets say I have data from two independent simulations. One of them look like this: The fitted curve is done by minimizing absolute difference between each data point and the curve. The fit ...
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28 views

Finding a distribution that fits different observations of data

I am observing session lengths on a network. I want to fit a distribution to the data that I have collected. I have data from two different observations (about a month apart). The plot below shows ...
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1answer
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Fitting data to a log-normal distribution [duplicate]

For a simulation study I've been trying to find an appropriate distribution for job handling times in R. I have a very large dataset of 77010 records (handling time in seconds). I've been exploring ...
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1answer
23 views

What is the number of iterations used to estimate the ARMA coefficient

If we are using the LSE "least square error" equation for getting the AR and MA terms: by getting the LSE in function of the coefficients and differencing it then equating it to zero.This yields ...
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1answer
171 views

Fit Hawkes process to 1d data using python package TICK

How can one fit the 1-dimensional Hawkes process with exponential kernel to the experimental 1d dataset (t1,t2,t3...tn) and check the goodness-of-fit via tick python3 package? I found on official ...
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1answer
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Fit a parametrized distribution on a set of quantiles

first of all, I'm not a statistician nor a data scientist, but a software developer. Thus, although I do have some (old) knowledge in statistics and probabilities, my vocabulary may not be very ...
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1answer
29 views

Why are mixed effect methods more effective when data are limited

In the study in here, it is said that mixed effects models are better in estimating parameters of a ODE system when there is only very small number of data to estimate the parameters. So, in a ...
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Fitting a distribution to data given only the tails? Fitting normal distribution from only the 90th-99th percentile of data [duplicate]

I'm trying something out in R and I'm curious how one would go about doing this. Let's say I have a sample of Americans and their income, furthermore I know that they are in the 90th-99th percentile ...
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1answer
45 views

test if two linear fits are different

I have time-dependent data from experiments done by two different labs. Lab1 has measurements at 60 different time-points. Lab2 has measurements at 40 different time-points (within the same range as ...
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2answers
642 views

Formal definition of the qqline used in a Q-Q plot

I'm doing some distribution fitting work and I'm looking at Q-Q plots and how they can be used visually to interpret goodness of fit. My data is heavy-tailed so I am looking at Weibull, log-normal, ...
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59 views

Generalized Additive Models: How to fit models with the LMS method by Cole?

I have some problems to understand the univariate generalized models that were proposed by Cole (1992). My question is how the fitting procedure works described in the appendix. More specific, how to ...
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Does conditional intensity function of some model must perfectly match with data intensity if model is true?

I consider some emperical dataset characterized by a single parameter - the arrival times of events {$t_0,t_1,t_2,...,t_i$} as is commonly adopted for point processes. The Hawkes model is tested for ...
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Fitting a system that transits between two time varying states

I have a system that transit between two different states. Each state output varies linearly with time, given by m*t+c, where both lines intersect the x axis in the same point. The output of this ...
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Fit Correction on known distributions

I'm looking for a way of correcting a linear fit through data. The scenario is the following: In red you have data points, they are based on uniformly distributed points on the black straight line ...