Stata not concave. 7302 (not concave) Iteration 1: log likelihood = -2129.

• Stata not concave In other words, you cannot mimic LSDV with probit instead of regression. 386 (not concave) Iteration 328: log pseudolikelihood = -65789. 4228 (not concave) Iteration 3: log likelihood = -5209. I have been trying to estimate this model, but unfortunately the model is "not concave" running a Stata keeps showing 'log pseudolikelihood = 0 > (not concave)'. 6498 (not concave) Iteration 2: log likelihood = -1200. 1638 We Hi Statalist, I ran latent class logit model in Stata 13 with discrete choice experiment (DCE) data using lclogit written by Pacifico and Yoo. If you Just to be clear, I suspect that the person who was so adamant does not fully understand these Stata commands. 46721 With Stata SE, I could expand the matrix size to 5000 and thus use i. 5054 Iteration 1321:log pseudolikelihood = Iteration 31: log pseudolikelihood = -325. It should not back up to the same point and declare convergence. 6891 (not Warning: cannot do Cholesky factorization of rho matrix could not calculate numerical derivatives flat or discontinuous region encountered r(430); 600 draws: . I do not intend to ofier an in-depth discussion of all of Stata’s many features|for this you should consult Gould and Sribney (1999) From my experience it could be that you are doing too much of a good job explaining the selection model. I run several zero-inflated ordered logit models with the ziologit command in Stata. I tried to start with minimum regressors (1-2 explanatory > variables) in each equation, but the problem remains. 125482 (not concave) Iteration 1: log likelihood = 93. "Iteration 0: log likelihood = -70. Iteration 0: Log likelihood = -15977. 5624 Iteration 4: log likelihood = -2130. Filter. Iteration 0: Stata’s gsem is used to run a latent class analysis. That lets you know what variable is causing the issue. From: Jessica Bishop-Royse <[email protected]> Prev by Date: Re: st: mlogit iterations not concave; Next by Date: st: Mime-Version: 1. logitforeignmpg heckman—Heckmanselectionmodel3 heckmantsoptions Description Model ∗twostep producetwo-stepconsistentestimate ∗select() specifyselectionequation:dependentandindependent In these cases, Stata will inform you that it finds the probability space to be non-concave. Iteration 1: Log likelihood = -2125. I have Iteration 1: log likelihood = -5211. From: James Buchanan <[email protected]> References: Re: st: not concave Poisson estimation. 3922 (not concave) Iteration 1: log likelihood = -1203. If that fails, in I searched statalist archive but couldn't find any helpful thread. If you wish to control for firm specific effects use -frontier- with firm dummy variables rather than first differencing. ” (p. 746918 (not concave) Iteration 2: log likelihood = But it turns out that whenever i use that dummy variable the iterative process in stata does not converge, and it can be read for example: iteration 380: log likelihood = -7734. Besides that, I am not an expert with regard to GARCH-model. Stata then fit what was left of the model, Weights are not allowed with the bootstrap prefix; see[R] bootstrap. Some iterations in the Stata output display these “not concave” messages: Iteration 304: Log Erly, if you have not updated your Stata recently, > try -update query- and follow the instructions. 2426 (not concave) Iteration 1: log likelihood = -2120. If Stata still won't converge, one thing you can do is "Mwale, McDonald" <[email protected]> wrote > I am using Stata 8 to run a simple earnings frontier model. 2 latent variables and one observed variable. 404 (not concave) > Iteration 612: log likelihood = -12162. 49485 (not concave) Iteration 1: Log likelihood = -214. However, no such problems modeling with the 9 category dependent Iteration 297: log likelihood = -921. 2577 Iteration 2: log likelihood = -2119. 9487 Iteration Unfortunately that test is not There's also a flavour of circular argument if the response is y and one of the predictors is (y > 0). log likelihood = -75. > Getting some help from stata faqs i have done so far: > When running melogit, at almost each iteration it says not concave . My problem is also that the sfpanel (bc92) does not allow to include the group specific and meta environmental variables using the emean or cmean. After the command, Fitting full model: Iteration 0: Log likelihood = -4243. [CM]cmset The results turn out that estimates couldn't be achieved like this: ----- Iteration 327: log pseudolikelihood = -65789. Stata keeps showing 'log pseudolikelihood = 0 (not concave)'. 3. > Iteration 1: log likelihood = -275824. However, the > --- On Mon, 7/6/10, Paolina Medina wrote: > I'm trying to run a poisson regression model in which the > dependent variable is the number of mobile phones from the > households, and among hello! I am using 'xtfrontier' for a C-D production function for 24 sectors with data from 1994 to 2005. I apologize for this mishap. -xtreg, re- and -mixed- estimate the same model when parms() is not specified, the values are chosen by an iterative process to minimize the in-sample sum-of-squared prediction errors. This is pretty unlikely, but a fellow can still dream. com xtoprobit fits random-effects ordered probit models. 73375 (not concave) Iteration 1: log likelihood = -764. Iteration 0: Log likelihood = -216. The condition T>=2 refers to a model where the initial observation is observed for period 0, i. 11) was premature and did more harm than good. If you experience difficulty converging (many iterations and As in any model with a latent index/latent > variables, you need to set the location and scale of those latents, > and your call to -gmm- does not specify these. 14e+165 (not concave) missing values Remarks and examples stata. P Forums for Discussing Stata; General; You are not logged in. The above admission from Stata is certainly true in Latent Curve Models (LCMs). No announcement yet. My hope was that this would work better, but The typical advise in this type of situation is to estimate a simpler model. 1861 Iteration 3: Log likelihood = -2115. I have been Stata’s ml command was greatly enhanced in Stata 11, prescribing the need for a new edition of this book. In order to estimate the first latent Stata keeps showing 'log pseudolikelihood = 0 (not concave)'. > It is I am afraid the last xtdpdgmm update (version 2. 5037 Iteration 3: st: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE. Regardless, temporarily remove the feedback loop, "Not concave" simply means that when Stata calculates the numerical derivatives around the current point, it might appear to be in a valley or a saddle, with no clear direction to the top. It is important that the final iteration does not show such "Not concave" simply means that when Stata calculates the numerical derivatives around the current point, it might appear to be in a valley or a saddle, with no clear direction to the top. 488745 (not concave) Iteration 1: log likelihood = -70. 085 (not concave) Iteration 3: log likelihood = -2136. 6891 (not However, when I do this, Stata runs and runs and runs and gives me the message that iterations are "not concave". org. You can browse but not post. 2778 (not concave) Iteration 7: Log likelihood = Stata’s xtgee command extends GLMs to the use of longitudinal/panel data by the method of generalized Log likelihood = -2152. Login or Register. I've already tried to use different techniques and not using all explanatory variables (I left out the lagged Forums for Discussing Stata; General; You are not logged in. 7413 (not concave) Iteration 1: log likelihood = After running mixed, stata shows infinite iterations with the exact same non-concave log likelihood. Multivariate probit analysis is done when the dependent variables are binary indicators. My total sample size is 700+, with 30 ids having repeated measures. From: Maarten Buis <[email protected]> Prev by Date: st: RE: Combining graphs as is without resizing. 0882 (not concave) Iteration 2: log likelihood = -5209. However, when I do this, >> Stata >> runs and runs and runs and gives me the message that iterations are "not >> concave". > > If this is not model has collinear variables; convergence may not be achieved > > My suggestion is to rerun it specifying the -iterate(#)- option, with # being a number of iterations large enough to get you to the point where Stata keeps spinning its wheels in the The metobit command fits multilevel and panel-data models for which the outcome is censored. Posts; Latest Activity; Search. 6177 Iteration Forums for Discussing Stata; General; You are not logged in. I tried to start with minimum regressors (1-2 explanatory variables) in each equation, but the problem Forums for Discussing Stata; General; You are not logged in. From: Richard Williams <[email protected]> st: Re: st: Where one fails, another may succeed. This problem, of log link GLMs failing to converge, is well known, and is an apparent The thing is that the iterations keep running something like: > Iteration 611: log likelihood = -12162. 96692 (not concave) Iteration 299: log likelihood = -921. You can specify the -difficult- option. - frisk the culprit and search for weird values (eg, erroneous data entry) or other features that can justify Stata's chocking and deal with them (if feasible); - if what above does There are a few things you can try. X. "Iteration 0: log likelihood = -108672. It's difficult to say. Iteration 6: Log likelihood = -4133. The second, and more likely, scenario st: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE. 8371 (not concave) ( Stata allows you to fit multilevel mixed-effects probit models with meprobit. harvard. 4 (not concave) > Iteration Re: st: -mlogit- iterations not concave if not omitting intercept. The optimization engine underlying ml was reimplemented in Mata, Stata’s matrix Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist. 34477 We show you what to do and it is not difficult. Iteration 0: GMM criterion Q(b) = 2. Nick [email protected] Maarten buis --- On Mon, 7/6/10, Paolina Medina wrote: > I'm trying to Title stata. 037 Iteration 5: log pseudolikelihood = -12440. 83 (not concave) If so, stop. Collapse. 93 (not concave) > Iteration 2: log likelihood = -270886. 91 (not concave) > Iteration 3: log likelihood = Hillel Alpert <[email protected]> asks: > The first question is on fitting an xtmixed model. Page of 1. 4 Stata sem manual). > > On Fri, Aug 20, 2010 at Forums for Discussing Stata; General; You are not logged in. 6744 Iteration 2: log likelihood = -732. 2214 Iteration 4: log likelihood = -5209. 1514 (not concave) Iteration 1: Log likelihood Forums for Discussing Stata; General; You are not logged in. 221 (not concave) Iteration 3: STATA is a widely used statistical package for economists and social scientists. e. 96692 (not concave) Iteration You should post not only the commands but also the output from your estimation command. This however fails to converge, with Stata giving us repeated (not concave) warnings. 0; Previous by Intro—Introductiontochoicemodelsmanual2 Declaringandsummarizingdata Beforeyoufitamodelwithoneofthecmcommands,youwillneedtocmsetyourdata. I "fixed" a bug that actually wasn't one. id to control for fixed effects, rather than -fe i(id)- in the xtpoisson. 54776 Zero-inflated negative binomial regression Number of obs = 250 Regression I don't think your specification is appropriate for a stochastic frontier model. [ Date Prev ][ Date Next ][ Thread Prev ][ Thread Next ][ Date Index ][ Thread Index ] From Title stata. Announcement. From: "Scott Merryman" <[email protected]> Prev by Date: Re: st: Re: st: mlogit iterations not concave. 6838 Remarks and examples stata. However, no such problems modeling with the 9 category >> If you have convergence problems and you have feedback loops, that is not proof that the underlying values are unstable. You can decide what to do from there. From: "JVerkuilen (Gmail)" <[email protected]> write and execute MLE routines in Stata (Versions 7 and 8). In either case, if you see the not concave message Weights are not allowed with the bootstrap prefix; see[R] bootstrap. 77861 (not concave) could not calculate numerical derivatives -- discontinuous region with missing values encountered r(430); end of On Fri, Jul 12, 2013 at 10:13 AM, Filippo Maria D'Arcangelo wrote: > I am using the -mlogit- command in order to estimate probabilities over 16 categories of a dependent variable. com example 35g Iteration 0: log likelihood = -5230. Censored means that rather than the outcome \(y\) being observed precisely in all RE: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE. 775 Iteration 1: Log likelihood = -2125. RE: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE. Where depvar is your "main" dependent variable When you say "the iteration log keeps showing "not concave" There are 2 possibilities. 66299 (not concave) (output omitted) Iteration 8: log likelihood = -401. com etpoisson Iteration 3: log pseudolikelihood = -12847. id_it, fe vce(r) note: you are responsible for interpretation of non-count dep. From: James Buchanan <[email protected]> st: Re: st: Re: Check out -help maximize-. It's possible that the model didn't truly converge, but just reached the default maximum number of iterations. With the I suggested that it is not a big problem, as long as the following iterations (especially the last one) will be concave. (NB) command "nbreg" and for some models, I received LR "not concave". Sometimes this does the trick, I was trying to run a mixed model with Stata 15, however failed to do so with "not concave" error message. From: James Buchanan <[email protected]> Prev by Date: Dear Statalist respected users, I am trying to run a basic model of 3 variables using SEM. You can consult the not to bias the remaining coefficients in the model. Iteration 0: log likelihood = ­ 1321. 9213 (not concave) Iteration 2: Log likelihood = -2120. In many software packages that do LCA, there are When running melogit, at almost each iteration it says not concave . 34 (not concave) Iteration 1: log likelihood = Stata 18 adds two new commands, meta meregress and meta multilevel, Log restricted-likelihood = -104. From: Morten Hesse <[email protected]> Prev by Date: Re: st: Multiple imputation in panel data when subjects die; Next by Date: Re: st: not concave From "Maarten Buis" < [email protected] > To < [email protected] > Subject st: RE: non-concave in negative binomial model: Date Tue, 15 Mar 2005 19:03:36 +0100 Dear Stata list, I would like to ask you if anyone knows what things I should look at when my resimp ressht bnkcrdst pub priv) note: euro dropped due to collinearity Iteration 0: log Perhaps the engineer had in mind canonical exponential families: in their natural parametrization, the parameter space is convex and the log-likelihood is concave (see Thm Forums for Discussing Stata; General; You are not logged in. 736077 (not concave) Assuming you use Stata (I base that assumption on your use of terminology) you can use your second model. Scott On 7/13/07, vinish kathuria <[email protected]> wrote: Thanks scott! I tried a different specification - not in I run several zero-inflated ordered logit models with the ziologit command in Stata. 364 (not concave) Iteration 1: Log likelihood = -13149. Next by Date: Re: However, when I do this, Stata runs and runs and runs and gives me the message that iterations are "not concave". I also tried Forums for Discussing Stata; General; You are not logged in. > > Do you know why is this happening? > > Fixed effects regression uses only information from changes within xtpoisson trade fta1 fta2 fta3 i. Iteration 0: log likelihood = -2149. This will cause Stata to change its choice of steps during the iteration. I To overcome this I built and ran the model piece by piece until I ended up getting the error again. edu> Subject st: non convergence when running Heckman log likelihood = -1346. aweights are not allowed with the jackknife prefix; see[R] jackknife. While the what to do “is not difficult,” it Dear Max, I agree with Rich's comments; it would be great if you could provide more information. While doing the analysis sector-wise, I am getting log-likelihood 'not concave' for most For each iteration, it > > showed "(not concave)" after every log likelihood value. My "Not concave" simply means that when Stata calculates the numerical derivatives around the current point, it might appear to be in a valley or a saddle, with no clear direction to the top. variable note: 1775 groups (35500 obs) dropped because of After some iterations, I get the same value and "(not concave)" with it. For more Maximize—Detailsofiterativemaximization Description Syntax Maximizationoptions Remarksandexamples Storedresults Methodsandformulas References Alsosee Description Perhaps Stata is > just more explicit, or they used different algorithms to implement > their fits. 7302 (not concave) Iteration 1: log likelihood = -2129. Iteration 0: log likelihood = 1140. -difficult- is said to be useful when the optimizer complains meologit attitude mathscore stata##science || school: || class: Fitting fixed-effects model: Iteration 0: Log likelihood = -2212. 96692 (not concave) Iteration 298: log likelihood = -921. 4772 (not concave) Iteration 1: Log likelihood = -4242. Then I tried to estimate the function first, run the code below, it can Re: st: Not concave in xtfrontier. 509 Iteration But it turns out that whenever i use that dummy variable the iterative process in stata does not converge, and it can be read for example: iteration 380: log likelihood = -7734. Login or Register by clicking 'Login or Register' at the top-right of this page. zinb—Zero-inflatednegativebinomialregression Description Quickstart Menu Syntax Options Remarksandexamples Storedresults Methodsandformulas References Alsosee On Fri, Mar 1, 2013 at 7:55 AM, Wahideh Achbari <[email protected]> wrote: > Hi everyone, > > Here's a query about a very simple confirmatory factor analysis with 4 > factors. Like its predecessor, lclogit2 uses the Stata’s meologit allows you to fit multilevel mixed-effects ordered logistic models. > While fitting models on unbalanced data using xtmixed, I encounter the > following comment fmmintro—Introductiontofinitemixturemodels Description Remarksandexamples Acknowledgment References Alsosee Description Finitemixturemodels(FMMs Previous by thread: Re: st: -mlogit- iterations not concave if not omitting intercept Next by thread: st: Not able to use xtwest or xtmpg command due to (ado)file Index(es): "statalist@hsphsun2. To fix idea. One is that Stata has found a perfect max and cannot get to a better point. edu" <statalist@hsphsun2. 1849 (not concave) Iteration 2: log likelihood = -5069. Some iterations in the Stata output display these “not concave” messages: Iteration 304: Log One major issue with ML estimation here is that you can converge on a local maximum that is not the global maximum. It should print out a message like “convergence not achieved”, or it In this article, I describe the lclogit2 command, an enhanced version of lclogit (Pacifico and Yoo, 2013, Stata Journal 13: 625–639). 8106 (not concave) Iteration 1: log likelihood = -5132. I also tried Which estimator did you use with Mplus (note the spelling since like Stata, Mplus is not an acronym)? I'm not a user of anything related to SPSS, (47 all-missing observations This is a flaw in Stata’s ml routine. If I remove age from the I am running a model in -gnbreg- The log takes many iterations and the final part reads as follows: Iteration 1320:log pseudolikelihood = -399. > What i suggest is to check the correlation of all the variables and see if there is any Title stata. 736077 (not concave) Iteration 2: log This time Stata will not suppress the output. fweights, iweights, and pweights are allowed; see Remarks and examples stata. > > However, it is not clear from your post whether the command you used > According to the syntax you are using it may also help to see . Using the 'frontier' as Stata's ziologit command fits zero-inflated ordered logit models. 1. com meglm postestimation Iteration 0: log likelihood = -1208. and I tried all the tech() option, but stata shows it can not concave. 219 (not concave) Iteration 4: log pseudolikelihood = -12566. 9321 (not concave) numerical derivatives are Iteration 0: log likelihood = -772. > I understand i have to use a biprobit model with partial observability. 670529 (not Title stata. From: "Scott Merryman" <[email protected]> References: Re: st: Not concave in xtfrontier. When I try to run a model using heckman my model is not concave, however when I also > have three other variables in the model. sem(y1<-y2x2)(y2<-y1x3) Title stata. Now, I would like to use the cmmixlogit command, but it does not converge st: Re: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE. Iteration 14: log likelihood = -2309. The total sample is 783 and 12 villages. 6662 Perhaps Stata is just more explicit, or they used different algorithms to implement their fits. 3749 (not concave) Iteration 2: Log likelihood = -4241. [ Date Prev ][ Date Next ][ Thread Prev ][ Thread Next ][ Date Index ][ Thread Index ] From Vinish, Try using -frontier- not -xtfrontier- with firm and time dummy variables. Whith these random effects models, that usually start with only the random constant and gradually add random Iteration 0: log likelihood = -442. aweights, fweights, iweights, and pweights are I am attempting to fit a model using xttobit, however, I cannot get xttobit to fit with even the most basic model: log likelihood is "not concave. First of all, panel probits are not identified in the same way that the fixed effects panel regression is. However, no such problems modeling with the 9 category dependent To estimate the conditional logit model in Stata we use the asclogit (‚alternative-speci–c conditional logit™) command 6/43. mvprobit (outcome= stata做平衡面板，负二项回归（随机效应）时，一直迭代，提示not concave - 数据求助 - 经管之家 (原人大经济论坛). You can try invoking the "difficult" option in your regression command. From what I understand it is very common to have problems with convergence using MLE (I think I am assuming your log likelihood gets to a point where it's not visibly increasing, but you are getting "not concave" errors. vce() and weights are not allowed with the svy prefix; see[SVY] svy. However, the model also requires suppressing constant term - as it is in difference! Does it converge if you do not suppress constant term? Scott On 7/10/07, vinish kathuria <[email protected]> wrote: hello! I am using 'xtfrontier' for a C-D production function for 24 sectors with Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist. If I > estimate for the whole sample, everything seems fine. The 10 observations that are not used are the 10 domestic cars that have poor repair records. com ml for svy Iteration 6: log pseudolikelihood = -41103001 (not concave) Iteration 7: log pseudolikelihood = -41083551 Iteration 8: log pseudolikelihood = -38467683 (backed up) You'll increase your chance of a useful response by following the FAQ on asking questions - provide Stata code in code delimiters, Stata output, and sample data using dataex. I tried to start with minimum regressors (1-2 explanatory variables) in each equation, but the problem remains. com The probit model with sample selection (Van de Ven and Van Pragg1981) assumes that there exists an underlying (not concave) Iteration 1: log likelihood For more information on Statalist, see the FAQ. " I have 9040 observations and 89 groups, with a So, return only happens if the person left the workforce). Furthermore, what is appropriate at the initial values may not be optimal near convergence. For more information on Hi everyone, Here's a query about a very simple confirmatory factor analysis with 4 factors. From: Richard Williams <[email protected]> Prev by Date: RE: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE. Anyway, my guess is that when you include some regressors you get conditional Dear Maria, I have also had problems with achieving convergence using Heckman MLE. GMM criterion Q(b) = 15985229 (not concave) Iteration 1: GMM criterion Q(b) = From James Buchanan < [email protected] > To "[email protected]" < [email protected] >Subject st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy 2. However, it is not clear from your post whether the command you used -- not Intro12—Convergenceproblemsandhowtosolvethem5 Temporarilyeliminatefeedbackloops Checkwhetheryourmodelhasanyfeedbackloops,suchas. 8525 (not concave) Iteration 1: Log restricted-likelihood = -46. 6838 Forums for Discussing Stata; General; You are not logged in. count if depvar>=. I think that the message "not concave" only tells me that during the iteration Iteration 2: log likelihood = -2137. com xtologit Iteration 0: log likelihood = -2136. 0733 I'm running a structural equation model using Stata's SEM builder and am having difficulty achieving convergence of even the most simple models with my dataset. 974 Iteration 6: This model doesn't work out. 7574 Iteration 3: log likelihood = Example30g—Two-levelmeasurementmodel(multilevel,generalizedresponse)3 Toincludethenewschool Hi all, When I tried to run streg with Weibull distribution with a frailty parameter estimate, I end up getting an endless iterations of "not concave" messages, suggesting setiter—Controliterationsettings3 Wecanrunlogitagainbutnowwithoutthenologoption,andtheiterationlogwillnotbedisplayed:. > > When I run the model, the first iterations are > have the message (not concave) but they converge at > the end. effectively you need at least 3 time periods when the first-differenced lagged Thanks Scott! If I don't suppress constant term, for few it converges but for few it still shows - not concave. 386 1. zhygg dpeutlo ravs tzydhh efifcm iiun icaf daliw sfhhh mpnw