MiX99. Heterogeneous residual variance. Timo Pitkänen, MTT. Solving Large Mixed Model Equations

Transcription

1 MiX99 Solving Large Mixed Model Equations Heterogeneous residual variance Timo Pitkänen, MTT

2 Outline What is heterogeneous residual variance Setting up instruction files for BLUP Variance component estimation DEMO This presentation focus on HOW to do things in MiX99 MTT Agrifood Research Finland

3 What is heterogeneous residual variance Heterogeneous residual variance means that observations within trait have a different residual co-variance matrices For example In test-day model residual variance may change during lactation or measurements are made in different protocol (AMS / CMS) MTT Agrifood Research Finland

4 Todo list for BLUP 1. Add integer column to data specifying the residual class 2. Modify instruction file 3. Create parameter file containing residual co-variance parameters 4. Run MiX99 to solve model MTT Agrifood Research Finland

5 Data edit Data should have an integer column specifying residual class used for a record Residual classes should be numbered from 1 to Nc, where Nc is total number of residual classes MTT Agrifood Research Finland

6 Modify instruction file TITLE Model with heterogeneous residual variance INTEGER INTEGER animal ANIMAL HERD MSCODE DIM RESCLASS... RESIDUAL RESIDUAL MSCODE RESCLASS RESIDFILE RESIDFILE residuals.parin PARFILE parameters.parin residual class variable parameter file for residuals parameter file for other variance components MTT Agrifood Research Finland

7 Parameter file for residual co-variance matrices for BLUP First column in parameter file describes residual class Second and third columns gives matrix position i,j Fourth column specifies variance component value The size of a matrix is N traits N traits MTT Agrifood Research Finland

8 Parameter file for residual co-variance matrices for BLUP Only non-zero elements have to be defined Parameter file for random effects should contain one residual matrix That matrix is not used for BLUP or VCE but it is needed for reliabilities MTT Agrifood Research Finland

9 Variance component estimation MTT Agrifood Research Finland

10 Todo list for VCE 1. Add integer column specifying the residual class to data 2. Modify instruction file 3. Create parameter file containing residual co-variance parameters 4. Specify VC parameters that should remain unchanged to solver option file, if any 5. Run MiX99 6. Data edit and instruction file changes are same as in BLUP MTT Agrifood Research Finland

11 Parameter file for VCE Parameter files are used as an initial values for variance component estimation All non-zero elements should be given When zero element is wanted to keep unchanged, it should be given in the parameter files MiX99s will constantly update VC estimates to files named parfile and resfile It is good idea to use different file names for starting values The residual matrix given in parfile will be replaced by the matrix of a first residual class MTT Agrifood Research Finland

12 Modification of solver option file # RAM: RAM demand H # STOP: e-10 d f # RESID: Calculate residuals? (Y/N) N # VALID: N=no, P=prediction, S=sum N # HETVAR: (N)o HV, (S)tart HV, (C)ontinue HV, (F)inale, (E)stimation VC by EM E F # STOPE maximum number of EM steps, samples/step, convergenc crit e-14 # RANDG random number generator D # mix99i /home/lst102/bin/ # /share/apps # TYPSOL: Solution files? (N)o, (Y)es, (A)itken, (H)alf-Chebychev Y Estimate variance components F if some variance components are kept unchanged Number of variance components kept unchanged List of fixed variance components, format: matrix number, i,j MTT Agrifood Research Finland

13 DEMO: Test-day model continues Example how to setup and estimate milking system specific residual co-variance matrix MTT Agrifood Research Finland