sessions/20160304.R
In squipbar/edsProjection: Implements polynomial projection on Maliar & Maliars's EDS grid
library(xtable)
library(scales)
### A Very simple parameter setting
params <- list( share = .75, gamma = 2, P1.bar=1, P2.bar=1, betta=.95,
rho=c(.25,.25), sig.eps=c(.03,.03), eta=1 )
sd.x <- params$sig.eps / sqrt( ( 1 - params$rho ^ 2 ) )
upper <- c( 3 * sd.x, rep( .1, 2 ) )
lower <- -upper
opt <- list( lags=1, n.exog=2, n.endog=2, n.cont=13, N=1, cheby=FALSE,
upper = upper, lower=lower, quad=TRUE, n.quad=3, burn=1000,
kappa=25, n.sim=10000, eps = .7, delta=.05, endog.init=c(0, 0),
c.iter=400, c.tol=1e-07, c.gain=.25,
k.iter=50, k.tol=2e-04, k.gain=.2,
n.iter=1, n.tol=1e-05, n.gain=.25,
tol=1e-05, iter=40, model='irbc',
sr=TRUE, adapt.gain=TRUE, adapt.exp=15, image=TRUE,
sym.reg=TRUE )
coeff.init <- matrix( .02, 5, 2 )
coeff.init[2,] <- c( -.01,.02)
coeff.init[3,] <- c( .02,-.01)
coeff.init[4,] <- c( -.02,.01)
coeff.init[5,] <- c( .01,-.02)
coeff.cont.init <- matrix( 0, 5, opt$n.cont )
c.ss <- params$share ^ params$share * ( 1 - params$share ) ^ ( 1 - params$share )
p.ss <- 1 / c.ss
coeff.cont.init[1, ] <- log( c( c.ss, c.ss, 1 / params$betta, 1 / params$betta,
params$share, params$share, 1 - params$share, 1 - params$share,
p.ss, p.ss, 1, 1, 1 ) )
coeff.cont.init[2, ] <- c( -.1, .5, -.2, .5, rep( .1, 9 ) ) / 10
coeff.cont.init[3, ] <- c( .5,-.1, .5,-.2, rep( .1, 9 ) ) / 10
coeff.cont.init[4, ] <- coeff.cont.init[2, ]
coeff.cont.init[5, ] <- coeff.cont.init[3, ]
opt$l.sym.ave <- list( sym=list(c(2,3),c(4,5) ), ave=c(1) )
opt$l.pairs <- list( c(1,2) )
opt$l.pairs.cont <- list( c(1,2), c(3,4), c(5,6), c(7,8), c(9,10), c(11,12) )
opt$sym.reg <- TRUE
# Rough solution
opt$iter <- 12
sol.irbc.N.1.b <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init, debug.flag = F )
# Finer solution
opt$n.gain <- .02
opt$iter <- 15
sol.irbc.N.1.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
rep.irbc.N.1.b <- report.data( sol.irbc.N.1.b )
report.create( sol.irbc.N.1.b, rep.irbc.N.1.b )
##### THIS WORKS !!!! ###
## Now: Find a nonlinear solution ##
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.N.1.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.N.1.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 20
# Try a nonlinear solution
sol.irbc.N.1.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
rep.irbc.N.1.b.nl <- report.data( sol.irbc.N.1.b.nl )
report.create( sol.irbc.N.1.b.nl, rep.irbc.N.1.b.nl )
### Now increase gamma ###
params$gamma <- 3
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .1
opt$iter <- 16
sol.irbc.2.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# This is about as good at the linear solution gets
opt$N <- 2
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.2.b$coeff
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.2.b$coeff.cont
opt$n.gain <- .03
opt$iter <- 60
sol.irbc.2.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Nonlinear solution
rep.irbc.2.b <- report.data( sol.irbc.2.b )
report.create( sol.irbc.2.b, rep.irbc.2.b )
rep.irbc.2.b.nl <- report.data( sol.irbc.2.b.nl )
report.create( sol.irbc.2.b.nl, rep.irbc.2.b.nl )
params$gamma <- 4
opt <- sol.irbc.2.b$opt
opt$n.gain <- .025
opt$iter <- 50
sol.irbc.3.b <- sol.irbc.iterate( sol.irbc.2.b$coeff, opt, params, sol.irbc.2.b$coeff.cont )
# This is about as good at the linear solution gets
opt <- sol.irbc.2.b.nl$opt
opt$k.gain <- .1
opt$k.iter <- 30
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.3.b$coeff
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.3.b$coeff.cont
sol.irbc.3.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Nonlinear solution
rep.irbc.3.b <- report.data( sol.irbc.3.b )
report.create( sol.irbc.3.b, rep.irbc.3.b )
rep.irbc.3.b.nl <- report.data( sol.irbc.3.b.nl )
report.create( sol.irbc.3.b.nl, rep.irbc.3.b.nl )
### Now increase rho ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .1
opt$iter <- 22
params$rho <- c( .75, .75 )
sol.irbc.4.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# Linear solution
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.4.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.4.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 40
opt$n.gain <- .1
sol.irbc.4.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Try a nonlinear solution
rep.irbc.4.b <- report.data( sol.irbc.4.b )
report.create( sol.irbc.4.b, rep.irbc.4.b )
rep.irbc.4.b.nl <- report.data( sol.irbc.4.b.nl )
report.create( sol.irbc.4.b.nl, rep.irbc.4.b.nl )
# Report
### Now increase sigma.eps ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .02
opt$iter <- 10
params$sig.eps <- c( .05, .05 )
sol.irbc.5.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# The linear solution. It is quite poor.
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.5.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.5.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 30
opt$n.gain <- .1
sol.irbc.5.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Try a nonlinear solution
rep.irbc.5.b <- report.data( sol.irbc.5.b )
report.create( sol.irbc.5.b, rep.irbc.5.b )
rep.irbc.5.b.nl <- report.data( sol.irbc.5.b.nl )
report.create( sol.irbc.5.b.nl, rep.irbc.5.b.nl )
# Report
### Now increase sigma.eps more ###
params$sig.eps <- c(.075,.075)
sd.x <- params$sig.eps / sqrt( ( 1 - params$rho ^ 2 ) )
upper <- c( 3 * sd.x, rep( .4, 2 ) )
lower <- -upper
opt <- sol.irbc.5.b$opt
opt$iter <- 27
opt$n.gain <- .075
opt$upper <- upper
opt$lower <- lower
sol.irbc.6.b <- sol.irbc.iterate( sol.irbc.5.b$coeff, opt, params, sol.irbc.5.b$coeff.cont )
# The linear solution.
opt <- sol.irbc.5.b.nl$opt
opt$n.gain <- .05
opt$iter <- 30
sol.irbc.6.b.nl <- sol.irbc.iterate( sol.irbc.5.b.nl$coeff, opt, params, sol.irbc.5.b.nl$coeff.cont )
# The nonlinear solution
rep.irbc.6.b <- report.data( sol.irbc.6.b )
report.create( sol.irbc.6.b, rep.irbc.6.b )
rep.irbc.6.b.nl <- report.data( sol.irbc.6.b.nl )
report.create( sol.irbc.6.b.nl, rep.irbc.6.b.nl )
# Report
### Now increase share ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .05
opt$iter <- 16
params$share <- .85
sol.irbc.7.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# Linear solution
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.7.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.7.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 30
opt$n.gain <- .05
opt$n.k <- 30
sol.irbc.7.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# The nonlinear solution
rep.irbc.7.b <- report.data( sol.irbc.7.b )
report.create( sol.irbc.7.b, rep.irbc.7.b )
rep.irbc.7.b.nl <- report.data( sol.irbc.7.b.nl )
report.create( sol.irbc.7.b.nl, rep.irbc.7.b.nl )
# Report
### Try eta > 1 ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .05
opt$iter <- 7
params$eta <- 1.5
sol.irbc.8.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# Linear solution
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.8.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.8.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 50
opt$n.gain <- .05
sol.irbc.8.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# The nonlinear solution
rep.irbc.8.b <- report.data( sol.irbc.8.b )
report.create( sol.irbc.8.b, rep.irbc.8.b )
rep.irbc.8.b.nl <- report.data( sol.irbc.8.b.nl )
report.create( sol.irbc.8.b.nl, rep.irbc.8.b.nl )
# Report
### Increase eta a little more ###
opt <- sol.irbc.8.b$opt
params$eta <- 1.75
opt$c.gain <- .05
opt$c.iter <- 50
# Actually prevents divergence in the control solution!
opt$adapt.exp <- 100
# Likewise
opt$n.gain <- .02
opt$k.gain <- .2
opt$iter <- 9
sol.irbc.9.b <- sol.irbc.iterate( sol.irbc.8.b$coeff, opt, params, sol.irbc.8.b$coeff.cont )
# Linear solution
opt$N <- 2
# opt$c.gain <- .1
# # Actually prevents divergence in the control solution!
# opt$adapt.exp <- 50
# # Likewise
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.9.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.9.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 25
sol.irbc.9.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
opt$n.gain <- .05
opt$adapt.exp <- 20
opt$iter <- 17
sol.irbc.9.b.nl <- sol.irbc.iterate( sol.irbc.9.b.nl$coeff, opt, params, sol.irbc.9.b.nl$coeff.cont )
opt$n.gain <- .05
opt$iter <- 10
sol.irbc.9.b.nl <- sol.irbc.iterate( sol.irbc.9.b.nl$coeff, opt, params, sol.irbc.9.b.nl$coeff.cont )
opt$n.gain <- .02
opt$iter <- 10
sol.irbc.9.b.nl <- sol.irbc.iterate( sol.irbc.9.b.nl$coeff, opt, params, sol.irbc.9.b.nl$coeff.cont )
# The nonlinear solution (do in several stages)
rep.irbc.9.b <- report.data( sol.irbc.9.b )
report.create( sol.irbc.9.b, rep.irbc.9.b )
rep.irbc.9.b.nl <- report.data( sol.irbc.9.b.nl )
report.create( sol.irbc.9.b.nl, rep.irbc.9.b.nl )
# Report
### Set eta=2 ###
opt <- sol.irbc.9.b$opt
params$eta <- 2
opt$iter <- 4
sol.irbc.10.b <- sol.irbc.iterate( sol.irbc.9.b$coeff, opt, params, sol.irbc.9.b$coeff.cont )
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.10.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.10.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 20
opt$adapt.exp <- 500
opt$c.iter <- 40
sol.irbc.10.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
opt$iter <- 30
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
opt$c.iter <- 20
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
# Nonlinear solution
rep.irbc.10.b <- report.data( sol.irbc.10.b )
report.create( sol.irbc.10.b, rep.irbc.10.b )
rep.irbc.10.b.nl <- report.data( sol.irbc.10.b.nl )
report.create( sol.irbc.10.b.nl, rep.irbc.10.b.nl )
squipbar/edsProjection documentation built on May 30, 2019, 8:22 a.m.
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library(xtable)
library(scales)
### A Very simple parameter setting
params <- list( share = .75, gamma = 2, P1.bar=1, P2.bar=1, betta=.95,
rho=c(.25,.25), sig.eps=c(.03,.03), eta=1 )
sd.x <- params$sig.eps / sqrt( ( 1 - params$rho ^ 2 ) )
upper <- c( 3 * sd.x, rep( .1, 2 ) )
lower <- -upper
opt <- list( lags=1, n.exog=2, n.endog=2, n.cont=13, N=1, cheby=FALSE,
upper = upper, lower=lower, quad=TRUE, n.quad=3, burn=1000,
kappa=25, n.sim=10000, eps = .7, delta=.05, endog.init=c(0, 0),
c.iter=400, c.tol=1e-07, c.gain=.25,
k.iter=50, k.tol=2e-04, k.gain=.2,
n.iter=1, n.tol=1e-05, n.gain=.25,
tol=1e-05, iter=40, model='irbc',
sr=TRUE, adapt.gain=TRUE, adapt.exp=15, image=TRUE,
sym.reg=TRUE )
coeff.init <- matrix( .02, 5, 2 )
coeff.init[2,] <- c( -.01,.02)
coeff.init[3,] <- c( .02,-.01)
coeff.init[4,] <- c( -.02,.01)
coeff.init[5,] <- c( .01,-.02)
coeff.cont.init <- matrix( 0, 5, opt$n.cont )
c.ss <- params$share ^ params$share * ( 1 - params$share ) ^ ( 1 - params$share )
p.ss <- 1 / c.ss
coeff.cont.init[1, ] <- log( c( c.ss, c.ss, 1 / params$betta, 1 / params$betta,
params$share, params$share, 1 - params$share, 1 - params$share,
p.ss, p.ss, 1, 1, 1 ) )
coeff.cont.init[2, ] <- c( -.1, .5, -.2, .5, rep( .1, 9 ) ) / 10
coeff.cont.init[3, ] <- c( .5,-.1, .5,-.2, rep( .1, 9 ) ) / 10
coeff.cont.init[4, ] <- coeff.cont.init[2, ]
coeff.cont.init[5, ] <- coeff.cont.init[3, ]
opt$l.sym.ave <- list( sym=list(c(2,3),c(4,5) ), ave=c(1) )
opt$l.pairs <- list( c(1,2) )
opt$l.pairs.cont <- list( c(1,2), c(3,4), c(5,6), c(7,8), c(9,10), c(11,12) )
opt$sym.reg <- TRUE
# Rough solution
opt$iter <- 12
sol.irbc.N.1.b <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init, debug.flag = F )
# Finer solution
opt$n.gain <- .02
opt$iter <- 15
sol.irbc.N.1.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
rep.irbc.N.1.b <- report.data( sol.irbc.N.1.b )
report.create( sol.irbc.N.1.b, rep.irbc.N.1.b )
##### THIS WORKS !!!! ###
## Now: Find a nonlinear solution ##
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.N.1.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.N.1.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 20
# Try a nonlinear solution
sol.irbc.N.1.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
rep.irbc.N.1.b.nl <- report.data( sol.irbc.N.1.b.nl )
report.create( sol.irbc.N.1.b.nl, rep.irbc.N.1.b.nl )
### Now increase gamma ###
params$gamma <- 3
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .1
opt$iter <- 16
sol.irbc.2.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# This is about as good at the linear solution gets
opt$N <- 2
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.2.b$coeff
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.2.b$coeff.cont
opt$n.gain <- .03
opt$iter <- 60
sol.irbc.2.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Nonlinear solution
rep.irbc.2.b <- report.data( sol.irbc.2.b )
report.create( sol.irbc.2.b, rep.irbc.2.b )
rep.irbc.2.b.nl <- report.data( sol.irbc.2.b.nl )
report.create( sol.irbc.2.b.nl, rep.irbc.2.b.nl )
params$gamma <- 4
opt <- sol.irbc.2.b$opt
opt$n.gain <- .025
opt$iter <- 50
sol.irbc.3.b <- sol.irbc.iterate( sol.irbc.2.b$coeff, opt, params, sol.irbc.2.b$coeff.cont )
# This is about as good at the linear solution gets
opt <- sol.irbc.2.b.nl$opt
opt$k.gain <- .1
opt$k.iter <- 30
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.3.b$coeff
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.3.b$coeff.cont
sol.irbc.3.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Nonlinear solution
rep.irbc.3.b <- report.data( sol.irbc.3.b )
report.create( sol.irbc.3.b, rep.irbc.3.b )
rep.irbc.3.b.nl <- report.data( sol.irbc.3.b.nl )
report.create( sol.irbc.3.b.nl, rep.irbc.3.b.nl )
### Now increase rho ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .1
opt$iter <- 22
params$rho <- c( .75, .75 )
sol.irbc.4.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# Linear solution
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.4.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.4.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 40
opt$n.gain <- .1
sol.irbc.4.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Try a nonlinear solution
rep.irbc.4.b <- report.data( sol.irbc.4.b )
report.create( sol.irbc.4.b, rep.irbc.4.b )
rep.irbc.4.b.nl <- report.data( sol.irbc.4.b.nl )
report.create( sol.irbc.4.b.nl, rep.irbc.4.b.nl )
# Report
### Now increase sigma.eps ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .02
opt$iter <- 10
params$sig.eps <- c( .05, .05 )
sol.irbc.5.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# The linear solution. It is quite poor.
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.5.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.5.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 30
opt$n.gain <- .1
sol.irbc.5.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# Try a nonlinear solution
rep.irbc.5.b <- report.data( sol.irbc.5.b )
report.create( sol.irbc.5.b, rep.irbc.5.b )
rep.irbc.5.b.nl <- report.data( sol.irbc.5.b.nl )
report.create( sol.irbc.5.b.nl, rep.irbc.5.b.nl )
# Report
### Now increase sigma.eps more ###
params$sig.eps <- c(.075,.075)
sd.x <- params$sig.eps / sqrt( ( 1 - params$rho ^ 2 ) )
upper <- c( 3 * sd.x, rep( .4, 2 ) )
lower <- -upper
opt <- sol.irbc.5.b$opt
opt$iter <- 27
opt$n.gain <- .075
opt$upper <- upper
opt$lower <- lower
sol.irbc.6.b <- sol.irbc.iterate( sol.irbc.5.b$coeff, opt, params, sol.irbc.5.b$coeff.cont )
# The linear solution.
opt <- sol.irbc.5.b.nl$opt
opt$n.gain <- .05
opt$iter <- 30
sol.irbc.6.b.nl <- sol.irbc.iterate( sol.irbc.5.b.nl$coeff, opt, params, sol.irbc.5.b.nl$coeff.cont )
# The nonlinear solution
rep.irbc.6.b <- report.data( sol.irbc.6.b )
report.create( sol.irbc.6.b, rep.irbc.6.b )
rep.irbc.6.b.nl <- report.data( sol.irbc.6.b.nl )
report.create( sol.irbc.6.b.nl, rep.irbc.6.b.nl )
# Report
### Now increase share ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .05
opt$iter <- 16
params$share <- .85
sol.irbc.7.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# Linear solution
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.7.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.7.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 30
opt$n.gain <- .05
opt$n.k <- 30
sol.irbc.7.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# The nonlinear solution
rep.irbc.7.b <- report.data( sol.irbc.7.b )
report.create( sol.irbc.7.b, rep.irbc.7.b )
rep.irbc.7.b.nl <- report.data( sol.irbc.7.b.nl )
report.create( sol.irbc.7.b.nl, rep.irbc.7.b.nl )
# Report
### Try eta > 1 ###
params <- sol.irbc.N.1.b$params
opt <- sol.irbc.N.1.b$opt
opt$n.gain <- .05
opt$iter <- 7
params$eta <- 1.5
sol.irbc.8.b <- sol.irbc.iterate( sol.irbc.N.1.b$coeff, opt, params, sol.irbc.N.1.b$coeff.cont )
# Linear solution
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.8.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.8.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 50
opt$n.gain <- .05
sol.irbc.8.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
# The nonlinear solution
rep.irbc.8.b <- report.data( sol.irbc.8.b )
report.create( sol.irbc.8.b, rep.irbc.8.b )
rep.irbc.8.b.nl <- report.data( sol.irbc.8.b.nl )
report.create( sol.irbc.8.b.nl, rep.irbc.8.b.nl )
# Report
### Increase eta a little more ###
opt <- sol.irbc.8.b$opt
params$eta <- 1.75
opt$c.gain <- .05
opt$c.iter <- 50
# Actually prevents divergence in the control solution!
opt$adapt.exp <- 100
# Likewise
opt$n.gain <- .02
opt$k.gain <- .2
opt$iter <- 9
sol.irbc.9.b <- sol.irbc.iterate( sol.irbc.8.b$coeff, opt, params, sol.irbc.8.b$coeff.cont )
# Linear solution
opt$N <- 2
# opt$c.gain <- .1
# # Actually prevents divergence in the control solution!
# opt$adapt.exp <- 50
# # Likewise
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.9.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.9.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 25
sol.irbc.9.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
opt$n.gain <- .05
opt$adapt.exp <- 20
opt$iter <- 17
sol.irbc.9.b.nl <- sol.irbc.iterate( sol.irbc.9.b.nl$coeff, opt, params, sol.irbc.9.b.nl$coeff.cont )
opt$n.gain <- .05
opt$iter <- 10
sol.irbc.9.b.nl <- sol.irbc.iterate( sol.irbc.9.b.nl$coeff, opt, params, sol.irbc.9.b.nl$coeff.cont )
opt$n.gain <- .02
opt$iter <- 10
sol.irbc.9.b.nl <- sol.irbc.iterate( sol.irbc.9.b.nl$coeff, opt, params, sol.irbc.9.b.nl$coeff.cont )
# The nonlinear solution (do in several stages)
rep.irbc.9.b <- report.data( sol.irbc.9.b )
report.create( sol.irbc.9.b, rep.irbc.9.b )
rep.irbc.9.b.nl <- report.data( sol.irbc.9.b.nl )
report.create( sol.irbc.9.b.nl, rep.irbc.9.b.nl )
# Report
### Set eta=2 ###
opt <- sol.irbc.9.b$opt
params$eta <- 2
opt$iter <- 4
sol.irbc.10.b <- sol.irbc.iterate( sol.irbc.9.b$coeff, opt, params, sol.irbc.9.b$coeff.cont )
opt$N <- 2
coeff.init <- matrix( 0, 15, 2 )
coeff.init[ c(1,2,4,7,11), ] <- sol.irbc.10.b$coeff
coeff.cont.init <- matrix( 0, 15, 13 )
coeff.cont.init[ c(1,2,4,7,11), ] <- sol.irbc.10.b$coeff.cont
opt$l.sym.ave <- list( sym=list( c(2,4), c(3,6), c(7,11), c(8,13), c(9,12), c(10,15) ),
ave=c(1,5,14) )
opt$iter <- 20
opt$adapt.exp <- 500
opt$c.iter <- 40
sol.irbc.10.b.nl <- sol.irbc.iterate( coeff.init, opt, params, coeff.cont.init )
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
opt$iter <- 30
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
opt$c.iter <- 20
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
sol.irbc.10.b.nl <- sol.irbc.iterate( sol.irbc.10.b.nl$coeff, opt, params, sol.irbc.10.b.nl$coeff.cont )
# Nonlinear solution
rep.irbc.10.b <- report.data( sol.irbc.10.b )
report.create( sol.irbc.10.b, rep.irbc.10.b )
rep.irbc.10.b.nl <- report.data( sol.irbc.10.b.nl )
report.create( sol.irbc.10.b.nl, rep.irbc.10.b.nl )
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