Error messages using LMER
Here is what happened using R-devel: ------------------------------------------------------------- EM iterations 0 85289.766 ( 5407.13: 0.0815) ( 26134.4: 0.00387) 1 84544.322 ( 333.732: 0.137) ( 1462.32: 0.00934) 2 84515.108 ( 129.506: 0.0270) ( 446.306: 0.00481) 3 84514.519 ( 115.592: 0.00355) ( 328.637: 0.00103) 4 84514.505 ( 113.981:0.000505) ( 311.160:0.000165) 5 84514.505 ( 113.755:7.45e-005) ( 308.524:2.50e-005) 6 84514.505 ( 113.722:1.11e-005) ( 308.128:3.77e-006) 7 84514.505 ( 113.717:1.66e-006) ( 308.068:5.66e-007) 8 84514.505 ( 113.716:2.50e-007) ( 308.059:8.49e-008) 9 84514.505 ( 113.716:3.74e-008) ( 308.058:1.27e-008) 10 84514.505 ( 113.716:5.62e-009) ( 308.058:1.91e-009) 11 84514.505 ( 113.716:8.43e-010) ( 308.058:2.87e-010) 12 84514.505 ( 113.716:1.27e-010) ( 308.058:4.31e-011) 13 84514.505 ( 113.716:1.90e-011) ( 308.057:6.47e-012) 14 84514.505 ( 113.716:2.86e-012) ( 308.057:9.73e-013) 15 84514.505 ( 113.716:4.25e-013) ( 308.057:1.44e-013) EM iterations 0 83740.342 ( 113.716: -0.0164) ( 308.057:0.000596) 1 83740.273 ( 121.512:-0.00121) ( 298.914:-3.24e-005) 2 83740.272 ( 122.131:-0.000111) ( 299.397:-1.24e-005) EM iterations 0 84011.546 ( 122.131:-0.00474) ( 299.397:-0.000265) 1 84011.539 ( 124.616:-0.000472) ( 303.415:-6.62e-005) 2 84011.539 ( 124.869:-5.58e-005) ( 304.433:-1.16e-005) EM iterations 0 84018.589 ( 124.869:-0.000139) ( 304.433:-1.81e-005) 1 84018.589 ( 124.944:-1.62e-005) ( 304.713:-3.26e-006) 2 84018.589 ( 124.953:-2.12e-006) ( 304.764:-5.23e-007) EM iterations 0 84018.611 ( 124.953:-2.38e-006) ( 304.764:-5.44e-007) 1 84018.611 ( 124.954:-3.25e-007) ( 304.772:-8.50e-008) 2 84018.611 ( 124.955:-4.66e-008) ( 304.773:-1.29e-008) EM iterations 0 84018.611 ( 124.955:-4.75e-008) ( 304.773:-1.30e-008) 1 84018.611 ( 124.955:-6.93e-009) ( 304.774:-1.97e-009) 2 84018.611 ( 124.955:-1.03e-009) ( 304.774:-2.96e-010) Warning messages: 1: optim or nlminb returned message See PORT documentation. Code (27) in: LMEopt(x = mer, value = cv) 2: optim or nlminb returned message See PORT documentation. Code (27) in: LMEopt(x = mer, value = cv) 3: optim or nlminb returned message See PORT documentation. Code (27) in: LMEopt(x = mer, value = cv) 4: optim or nlminb returned message See PORT documentation. Code (27) in: LMEopt(x = mer, value = cv) 5: optim or nlminb returned message See PORT documentation. Code (27) in: LMEopt(x = mer, value = cv) 6: optim or nlminb returned message See PORT documentation. Code (27) in: LMEopt(x = mer, value = cv) 7: nlminb failed to converge in: lmer(.D ~ offset(log(.Y)) + (1 | provn) + (1 | bcohort) + agri + ------------------------------------------------------------- Shige
On 8/19/05, Shige Song <shigesong at gmail.com> wrote:
Dear Professor Bates, Here is output R 2.1.1 produced with "control = list(EMverbose = TRUE, msVerbose = TRUE)". I am getting the new devel version and see what will hapen there: -------------------------------------------------------------------------------- EM iterations 0 85289.766 ( 5407.13: 0.0815) ( 26134.4: 0.00387) 1 84544.322 ( 333.732: 0.137) ( 1462.32: 0.00934) 2 84515.108 ( 129.506: 0.0270) ( 446.306: 0.00481) 3 84514.519 ( 115.592: 0.00355) ( 328.637: 0.00103) 4 84514.505 ( 113.981:0.000505) ( 311.160:0.000165) 5 84514.505 ( 113.755:7.45e-005) ( 308.524:2.50e-005) 6 84514.505 ( 113.722:1.11e-005) ( 308.128:3.77e-006) 7 84514.505 ( 113.717:1.66e-006) ( 308.068:5.66e-007) 8 84514.505 ( 113.716:2.50e-007) ( 308.059:8.49e-008) 9 84514.505 ( 113.716:3.74e-008) ( 308.058:1.27e-008) 10 84514.505 ( 113.716:5.62e-009) ( 308.058:1.91e-009) 11 84514.505 ( 113.716:8.43e-010) ( 308.058:2.87e-010) 12 84514.505 ( 113.716:1.27e-010) ( 308.058:4.31e-011) 13 84514.505 ( 113.716:1.90e-011) ( 308.057:6.47e-012) 14 84514.505 ( 113.716:2.86e-012) ( 308.057:9.73e-013) 15 84514.505 ( 113.716:4.25e-013) ( 308.057:1.44e-013) iter 0 value 84514.505044 final value 84514.505044 converged EM iterations 0 83740.342 ( 113.716: -0.0164) ( 308.057:0.000596) 1 83740.273 ( 121.512:-0.00121) ( 298.914:-3.24e-005) 2 83740.272 ( 122.131:-0.000111) ( 299.397:-1.24e-005) iter 0 value 83740.272232 final value 83740.272232 converged EM iterations 0 84011.550 ( 122.204:-0.00461) ( 299.576:-0.000256) 1 84011.543 ( 124.624:-0.000459) ( 303.453:-6.41e-005) 2 84011.543 ( 124.870:-5.42e-005) ( 304.440:-1.13e-005) iter 0 value 84011.543350 final value 84011.543350 converged EM iterations 0 84018.592 ( 124.915:-6.44e-005) ( 304.548:-1.22e-005) 1 84018.592 ( 124.949:-8.29e-006) ( 304.737:-1.99e-006) 2 84018.592 ( 124.954:-1.15e-006) ( 304.768:-3.08e-007) iter 0 value 84018.591624 final value 84018.591624 converged EM iterations 0 84018.612 ( 124.955:3.40e-007) ( 304.770:-1.98e-007) 1 84018.612 ( 124.955:-9.98e-009) ( 304.773:-2.23e-008) 2 84018.612 ( 124.955:-5.47e-009) ( 304.774:-2.86e-009) iter 0 value 84018.611512 final value 84018.611512 converged Error in fn(par, ...) : Unable to invert singular factor of downdated X'X In addition: Warning message: Leading minor of size 8 of downdated X'X is indefinite -------------------------------------------------------------------------------- Thanks! Shige On 8/18/05, Douglas Bates <dmbates at gmail.com> wrote:
On 8/18/05, Shige Song <shigesong at gmail.com> wrote:
Dear All, After playing with lmer for couple of days, I have to say that I am amazed! I've been using quite some multilevel/mixed modeling packages, lme4 is a strong candidate for the overall winner, especially for multilevel generzlized linear models. Now go back to my two-level poisson model with cross-classified model. I've been testing various different model specificatios for the past couple of days. Here are the models I tried: 1) Two level random intercept model with level-1 covariates only m1 <- lmer(.D ~ offset(log(.Y)) + (1|provn) +(1|bcohort) + x1 + x2 , data, poisson, method="Laplace") 2) Two-level random intercept model with both level-1 and level-2 covariates, but no cross-level interactions: m2 <- lmer(.D ~ offset(log(.Y)) + (1|provn) +(1|bcohort) + x1 + x2 + z1 + z2, data, poisson, method="Laplace") 3) Two-level random intercept with cross-level interaction m3 <- lmer(.D ~ offset(log(.Y)) + (1|provn) +(1|bcohort) + x1 + x2 + z1 + z2 + x1:z1 + x2:z2, data, poisson, method="Laplace") Both model 1 and 2 run fine. For model 3, I got error message: ---------------------------------- Error in fn(par, ...) : Unable to invert singular factor of downdated X'X In addition: Warning messages: 1: optim or nlminb returned message ERROR: ABNORMAL_TERMINATION_IN_LNSRCH in: LMEopt(x = mer, value = cv) 2: Leading minor of size 1 of downdated X'X is indefinite ---------------------------------- What is going on here? Any workarounds? Thanks!
The first thing I would try is set the EMverbose and msVerbose flags in the control list to see what occurs within the optimization. That is append the argument control = list(EMverbose = TRUE, msVerbose = TRUE) to your call to lmer(). You may also want to try the call in a recently compiled R-devel, which will be released as R-2.2.0 in October. You will notice that the first warning message reads "optim or nlminb". In R-2.1.1 lmer uses optim for the optimization. Starting with R-2.2.0 the default is to use nlminb. Test compilations of R-devel for Windows are available from CRAN.