Description Usage Arguments Value References Examples
This function implement Markov chain Monte Carlo methods for the C4 photosynthesis model of Collatz et al. The chain is constructed using a Gaussian random walk. This is definitely a beta version of this function and more testing and improvements are needed. The value of this function is in the possibility of examining the empirical posterior distribution (i.e. vectors) of the vmax and alpha parameters. Notice that you will get different results each time you run it.
1 2 3 4 5 |
data |
observed assimilation data, which should be a data frame or matrix. The first column should be observed net assimilation rate (micro mol per meter squared per secondmicro mol per meter squared per second). The second column should be the observed quantum flux (micro mol per meter squared per secondmicro mol per meter squared per second). The third column should be observed temperature of the leaf (Celsius). The fourth column should be the observed relative humidity in proportion (e.g. 0.7). |
niter |
number of iterations to run the chain for (default = 20000). |
ivmax |
initial value for Vcmax (default = 39). |
ialpha |
initial value for alpha (default = 0.04). |
ikparm |
initial value for kparm (default = 0.7). Not optimized at the moment. |
itheta |
initial value for theta (default = 0.83). Not optimized at the moment. |
ibeta |
initial value for beta (default = 0.93). Not optimized at the moment. |
iRd |
initial value for dark respiration (default = 0.8). |
Catm |
see |
b0 |
see |
b1 |
see |
StomWS |
see |
ws |
see |
scale |
This scale parameter controls the size of the standard deviations which generate the moves in the chain. |
sds |
Finer control for the standard deviations of the prior normals. The first element is for vmax and the second for alpha. |
prior |
Vector of length 4 with first element prior mean for vmax, second element prior standard deviation for vmax, third element prior mean for alpha and fourth element prior standard deviation for alpha. |
an object of class MCMCc4photo
with components
Brooks, Stephen. (1998). Markov chain Monte Carlo and its application. The Statistician. 47, Part 1, pp. 69-100.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## Not run:
## Using Beale, Bint and Long (1996)
data(obsBea)
## Different starting values
resB1 <- MCMCc4photo(obsBea, 100000, scale=1.5)
resB2 <- MCMCc4photo(obsBea, 100000, ivmax=25, ialpha=0.1, scale=1.5)
resB3 <- MCMCc4photo(obsBea, 100000, ivmax=45, ialpha=0.02, scale=1.5)
## Use the plot function to examine results
plot(resB1,resB2,resB3)
plot(resB1,resB2,resB3,plot.kind='density',burnin=1e4)
## End(Not run)
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