我正在用R中的昆虫生物量每小时数据进行AICc分析，以找出我测量的哪种环境预测因子对生物量的影响最大。我正在使用Gamma发行版和一个“日志”作为模型竞赛的链接功能。除了我的null模型之外，我的所有模型都在收敛。我仍然在努力理解为什么这是一个hapenning。有人有想法吗？这是我在R中的代码：
我的数据是什么样的：
> str(insectnona)
'data.frame': 76 obs. of 28 variables:
$ TIME : Factor w/ 7 levels "2016_6","2016_7",..: 4 6 7 3 2 4 6 7 2 3 ...
$ JULIAN : Factor w/ 28 levels "147","148","149",..: 3 9 23 24 16 2 11 20 10 19 ...
$ SITE : Factor w/ 8 levels "1","3","5","12",..: 1 1 1 1 2 3 3 3 4 4 ...
$ HABITAT : Factor w/ 3 levels "C","E","F": 1 1 1 1 1 1 1 1 1 1 ...
$ TEMP_CIVIL : num 17.8 18.9 21.1 15 16 ...
$ BIO_ZONE : Factor w/ 3 levels "ESSFwh3","ICHdw1",..: 2 2 2 2 2 2 2 2 1 1 ...
$ AGE_CLASS : Factor w/ 3 levels "6","7","8": 2 2 2 2 2 1 1 1 3 3 ...
$ RICHNESS : int 4 9 9 9 8 6 8 8 3 2 ...
$ ARANEAE_Btot: num 0 0.1 0.1 6.9 3.73 ...
$ COL_Btot : num 2152.4 66.8 88.4 6.9 80.4 ...
$ DIP_Btot : num 72.8 39.6 17.7 20.9 132.4 ...
$ EPH_Btot : num 0 0 0 10.2 0.0333 ...
$ HEM_Btot : num 0 0.1 18.5 0 0 ...
$ HOM_Btot : num 0 14.9 30 6.2 0 ...
$ HYM_Btot : num 40.9 65.6 36.5 38 36.7 ...
$ LEP_Btot : num 161 2625 696 390 869 ...
$ NEU_Btot : num 0 0.1 3 15.5 10.6 ...
$ ORT_Btot : num 0 24.8 0 0 0 0 0 0 0 0 ...
$ PSO_Btot : num 0 0 0 0 0 0 9.3 0 0 0 ...
$ THY_Btot : num 0 0 0 0 0 0 0 0 0 0 ...
$ TRI_Btot : num 0 0 34.5 20.3 4.4 ...
$ BIOMASS_tot : num 2427 2837 924 515 1138 ...
$ OTHER_Btot : num 114 145 140 118 188 ...
$ COL_bhr : num 321.254 10.603 10.914 0.843 11.518 ...
$ LEP_bhr : num 24.1 416.7 85.9 47.7 124.5 ...
$ BIOMASS_hr : num 362.3 450.3 114.1 62.9 162.9 ...
$ RICHNESS_hr : num 0.597 1.429 1.111 1.1 1.146 ...
$ sTEMP_CIVIL : num 0.6228 0.8304 1.263 0.0796 0.2736 ...
我的模特比赛：
modl <- list()
modl[[1]]=glmer(BIOMASS_hr~AGE_CLASS + HABITAT + (1|SITE) + (1|TIME), data=insectnona,family="Gamma"(link="log") )
modl[[2]]=glmer(BIOMASS_hr~HABITAT + (1|SITE) + (1|TIME), data=insectnona,family="Gamma"(link="log") )
modl[[3]]=glmer(BIOMASS_hr~AGE_CLASS + (1|SITE) + (1|TIME), data=insectnona,family="Gamma"(link="log") )
modl[[4]]=glmer(BIOMASS_hr~BIO_ZONE + (1|SITE) + (1|TIME), data=insectnona,family="Gamma"(link="log") )
modl[[5]]=glmer(BIOMASS_hr~sTEMP_CIVIL + (1|SITE) + (1|TIME), data=insectnona,family="Gamma"(link="log") )
modl[[6]]=glmer(BIOMASS_hr~AGE_CLASS + HABITAT + sTEMP_CIVIL + (1|SITE) + (1|TIME), data=insectnona,family="Gamma"(link="log") )
modl[[7]]=glmer(BIOMASS_hr~HABITAT + sTEMP_CIVIL + (1|SITE) + (1|TIME),data=insectnona,family="Gamma"(link="log") )
modl[[8]]=glmer(BIOMASS_hr~HABITAT + BIO_ZONE + (1|SITE) + (1|TIME),data=insectnona,family="Gamma"(link="log") )
modl[[9]]=glmer(BIOMASS_hr~AGE_CLASS + HABITAT + BIO_ZONE + (1|SITE) +(1|TIME),data=insectnona,family="Gamma"(link="log") )
modl[[10]]=glmer(BIOMASS_hr~1 + (1|SITE) + (1|TIME),data=insectnona,family="Gamma"(link="log"))
aictab(modl)
然后我只为null模型（模型10）收到此警告消息：
Warning message: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model failed to converge with max|grad| = 0.0169244 (tol = 0.001, component 1)
提前感谢您的帮助！