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Table 4 Convergence diagnostics (95% quantile of potential scale reduction factor) for parameters of the asymmetric size-dependent competition model fitted to data for the 15 studied stands of Quercus robur

From: Tree potential growth varies more than competition among spontaneously established forest stands of pedunculate oak (Quercus robur)

Forest stand

g m

x 0

x b

a

β

σ

ϕ

A

1.05

1.06

1.03

1.03

1.04

1.00

1.00

B

1.01

1.01

1.00

1.01

1.02

1.00

1.01

C

1.00

1.00

1.00

1.01

1.01

1.00

1.00

D

1.00

1.05

1.06

1.10

1.11

1.00

1.00

E

1.01

1.00

1.00

1.01

1.00

1.00

1.00

F

1.02

1.03

1.02

1.02

1.02

1.00

1.00

G

1.00

1.00

1.00

1.04

1.04

1.00

1.00

H

1.00

1.04

1.03

1.01

1.00

1.00

1.00

I

1.03

1.02

1.02

1.06

1.07

1.00

1.01

K

1.01

1.08

1.04

1.01

1.03

1.00

1.01

L

1.00

1.02

1.05

1.00

1.00

1.00

1.00

M

1.01

1.01

1.01

1.06

1.05

1.00

1.00

O

1.00

1.01

1.00

1.00

1.00

1.00

1.00

P

1.02

1.04

1.03

1.01

1.00

1.00

1.00

Q

1.00

1.01

1.01

1.02

1.02

1.00

1.00

  1. Approximate convergence of the Markov chain Monte Carlo algorithm is diagnosed when the 95% quantile of potential scale reduction factor is close to 1. See Table 1 for parameter definition