Maximum Likelihood Estimation in Forest Growth Models with Measurement Errors

Sammanfattning

The forest growth model with measurement errors is introduced. The maximum likelihood estimates (MLE) of the parameters of this model are proven to be consistent and asymptotically normally distributed. The model is applied to the real data from Swedish National Forest Inventory and the MLE of the parameters are obtained

Nyckelord

Forest growth model; maximum likelihood estimation; random optimization

Publicerad i

Research report (Centre of Biostochastics)
2003, Volym: 2003, nummer: 3, sidor: 1-10 Utgivare: SLU

SLU författare

• Teterukovsky, Alex

  • Institutionen för skogsekonomi, Sveriges lantbruksuniversitet
    

• Ranneby, Bo

  • Institutionen för skogsekonomi, Sveriges lantbruksuniversitet
    

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/136