机器算法验证 - Lmer 模型无法收敛 - 吾爱随笔录

此处描述了我的数据拟合重复测量方差分析时，什么会导致 aov 中的“Error() 模型是奇异错误”？

我正在尝试使用以下方式查看交互的效果，lmer因此我的基本情况是：

my_null.model <- lmer(value ~ Condition+Scenario+ 
                             (1|Player)+(1|Trial), data = my, REML=FALSE)

my.model <- lmer(value ~ Condition*Scenario+ 
                             (1|Player)+(1|Trial), data = my, REML=FALSE)

运行anova给了我显着的结果，但是当我尝试考虑随机斜率 ( (1+Scenario|Player)) 时，模型失败并出现以下错误：

  Warning messages:
 1: In commonArgs(par, fn, control, environment()) :
   maxfun < 10 * length(par)^2 is not recommended.
 2: In optwrap(optimizer, devfun, getStart(start, rho$lower, rho$pp),  :
  convergence code 1 from bobyqa: bobyqa -- maximum number of function evaluations exceeded
 3: In commonArgs(par, fn, control, environment()) :
  maxfun < 10 * length(par)^2 is not recommended.
 4: In optwrap(optimizer, devfun, opt$par, lower = rho$lower, control = control,  :
   convergence code 1 from bobyqa: bobyqa -- maximum number of function evaluations exceeded
 5: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
   Model failed to converge with max|grad| = 36.9306 (tol = 0.002)
 6: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
   Model failed to converge: degenerate  Hessian with 1 negative eigenvalues

或者，如果它在多次迭代后未能收敛（我将其设置为100 000）并且之后我得到相同的结果50k，100k这意味着它非常接近实际值，只是没有达到它。那么我可以像这样报告我的结果吗？

请注意，当我将迭代设置得如此之高时，我只会收到以下警告：

 Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
 Model failed to converge with max|grad| = 43.4951 (tol = 0.002)
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
 Model failed to converge: degenerate  Hessian with 1 negative eigenvalues