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Questions tagged [convergence]

303 questions
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Why will glm model converge but caret train version of the same model will not?

As far as I can tell, I have specified this simple GLM the same way using a basic glm function and the caret train function. However, the caret version will not converge. Is there something missing in how I am specifying the train…
canderson156
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Convergence error code = 1 message = false convergence (8)

The convergence problem is something I never came to understand entirely, but I as far as I know, there are some keys in the code to get the model to convergence I am not attaching all the database because long-format exceeds the limits here. I…
Javier Hernando
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MATLAB error handling of SIMULINK (sim) due to external component

My problem is that I am running a sweep study with some parameters. I change them in MATLAB and then run a simulation in MATLAB with the sim command. The simulation in SIMULINK contains an external software component from COMSOL with an FEM behind…
jommil
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How to fix model convergence error in glmer code?

I am in the process of trying to run the following code and am continuously getting the same error: > model5 <- glmer(violentyn~vpul + bmi_new + wmax + (1|fid), data = cohort4, family = binomial) Warning messages: 1: In checkConv(attr(opt,…
Bridget
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MCMCglmm model repeats with discrete data giving different outputs each time

I am running MCMCglmm regressions to test for an interaction between two traits whilst accounting for phylogenetic influence. Both of my fixed effects are discrete (they are binary 0 or 1), here is a sample of my data: Genus CP Stripes genus1 1 …
Callum_mc
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ConvergenceWarning: Regressors in active set degenerate

I am running various Regressions in Python with lots of variables. For a more sparse variable selection, I implemented a relaxed Lasso (https://relaxedlasso.readthedocs.io/en/latest/content.html#implementation). The code works all fine and I get a…
z1313
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convergence problems with random effects negative binomial panel model

I'm trying to explain the count of new organization foundings in different countries over time. In my research area Stata is still very common, I thus need to be able to produce with R the results that stata would produce. Following this SO post,…
swhalemwo
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Fixing convergence issues with applying random effect modeling to multiply imputed longitudinal data

I am trying to run a random effects model using longitudinal data with repeated measures. I used MICE to impute the missing values and created 20 MI data sets. When running the model(s), I am given the following warnings: Warning: Model failed to…
Ryan Keen
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My simple tensorflow isn't converged out of the bp

Im new to tensorflow,and when I check the output, I find that the Lenet isn't converged.... So I think it may be caused by the failure of backward propagation.... I think the main problem is in the set of session, but .I can't find it... My code…
Lvaoao
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Running a linear mixed model regression when a zero-sum dependent variable causes near-zero variance in random effects

I just want to preface this by saying I'm very new to R, so I'm sorry if this has been answered else-where but I can't seem to see this situation address anywhere else with my limited theory/technical knowledge. Context: my data is from 60…
bedbedbedbedbedbed
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Lasso via GridSearchCV: ConvergenceWarning: Objective did not converge

I am trying to find the optimal parameter of a Lasso regression: alpha_tune = {'alpha': np.linspace(start=0.000005, stop=0.02, num=200)} model_tuner = Lasso(fit_intercept=True) cross_validation = RepeatedKFold(n_splits=5, n_repeats=3,…
NC520
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Why do I need a very high learning rate for this model to converge?

I have a simple model in tensorflow which is being trained on the first 1000 images in the MNIST datset. From my previous experience the learning rates which I used were of the order of around 0.001, however for my model to converge the learning…
finlay morrison
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Convergence rate adaptive Runge Kutta methods

I have a system of ODEs and I solve them with two different algorithms: A normal, constant stepsize, Runge Kutta 4 implementation A modified Runge Kutta 4, with variable stepsize control My professor asked me to make a plot showing convergences…
Lorenzo Teodorani
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Reduce error and finding convergence with numerical integration in R

I am trying to carry out a 1D numerical integration of the probability2DBox_free_t function here below: prob1Dbox<-function(invL, t, invtau, x0, x, n_lim) { c = pi * (pi/4) * (t * invtau) res = 0 for(n in 1:n_lim){ res = res + (exp(-1…
CafféSospeso
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Why is k-means converging in just one iteration?

I'm trying to do some k-means clustering but mu algorithm is converging to just one iteration. Xnorm=mms.fit_transform(dataML) cluster_centers = [meanC01, meanC02, meanC03, meanC04] km = KMeans(n_clusters=4,max_iter=30,random_state=42) …
P.Brito
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