search for: error_3

...ed_asm.nasm 2002-09-17 16:19:08.000000000 +0200 @@ -76,107 +76,73 @@ push edi sub esp, byte 16 ; qword [esp] == temp space for loading FLAC__uint64s to FPU regs - ; dword [esp] == last_error_0 - ; dword [esp + 4] == last_error_1 - ; dword [esp + 8] == last_error_2 - ; dword [esp + 12] == last_error_3 - ; eax == error ; ebx == &data[i] ; ecx == loop counter (i) - ; edx == temp - ; edi == save ; ebp == order ; mm0 == total_error_1:total_error_0 - ; mm1 == total_error_3:total_error_2 - ; mm2 == 0:total_error_4 - ; mm3/4 == 0:unpackarea - ; mm5 == abs(error_1):abs(error_0) - ; mm5 ==...

...,5) segment3=-40+0.5*1:15+rnorm(15,0,1) group=c(rep(1,20),rep(2,30),rep(3,15)) y=c(segment1,segment2,segment3) Data=data.frame(y,t=1:65,group=as.factor(group)) the model I'd like to fit is: y_t= (beta_01+beta_11*t+error_1)*(group==1)+(beta_02+beta_12*t+error_2)*(group==2)+(beta_03+beta_13*t+error_3)*(group==3) It looks like a mixed effects model were the fixed effect are the piecewise linear regression parts (beta_0i+beta_1i*t) and the random effects are the variance components error_i. The problem is that I can't find the way the write this model correctly using the lme() function of...