[Yuima-commits] r396 - pkg/yuima/man

[noreply at r-forge.r-project.org]

Author: hirokimasuda
Date: 2016-01-14 04:35:22 +0100 (Thu, 14 Jan 2016)
New Revision: 396

Modified:
   pkg/yuima/man/setModel.Rd
Log:
minor bug fixed

Modified: pkg/yuima/man/setModel.Rd
===================================================================
--- pkg/yuima/man/setModel.Rd	2016-01-14 03:34:49 UTC (rev 395)
+++ pkg/yuima/man/setModel.Rd	2016-01-14 03:35:22 UTC (rev 396)
@@ -122,8 +122,8 @@
 
 # Ex 2. (Two-dimensional diffusion process with three factors)
 # To describe
-# dX1t = -3*X1t*dt + dW1t +x2t*dW3t,
-# dX2t = -(X1t + 2*X2t)*dt + x1t*dW1t + 3*dW2t,
+# dX1t = -3*X1t*dt + dW1t +X2t*dW3t,
+# dX2t = -(X1t + 2*X2t)*dt + X1t*dW1t + 3*dW2t,
 # we set the drift coefficient
 a <- c("-3*x1","-x1-2*x2")
 # and also the diffusion coefficient
@@ -136,20 +136,41 @@
 # If the dimensions of the drift differs from the number of the rows of the diffusion, 
 # the error message is returned.
 
-# Ex 3. (Process with jumps)
-## specify the jump term as c(x,t)dz
-mod3 <- setModel(drift=c("-theta*x"), diffusion="sigma",
+# Ex 3. (Process with jumps (compound Poisson process))
+# To describe
+# dXt = -theta*Xt*dt+sigma*dZtmod3 <- setModel(drift=c("-theta*x"), diffusion="sigma",
 jump.coeff="1", measure=list(intensity="1", df=list("dnorm(z, 0, 1)")),
 measure.type="CP", solve.variable="x")
 # Look at the model structure by
 str(mod3)
 
-# Ex 4. (Process with fractional Gaussian noise)
+# Ex 4. (Process with jumps (stable process))
+# To describe
+# dXt = -theta*Xt*dt+sigma*dZt
+mod4 <- setModel(drift=c("-theta*x"), diffusion="sigma",
+jump.coeff="1", measure.type="code",measure=list(df="rstable(z,1,0,1,0)"), solve.variable="x")
+# Look at the model structure by
+str(mod4)
+# See rng about other candidate of Levy noises.
+
+# Ex 5. (Two-dimensional stochastic differenatial equation with Levy noise)
+# To describe
+# dX1t = (1 - X1t - X2t)*dt+dZ1t 
+# dX2t = (0.5 - X1t - X2t)*dt+dZ2t
+beta<-c(.5,.5)
+mu<-c(0,0)
+Lambda<-matrix(c(1,0,0,1),2,2)
+mod5 <- setModel(drift=c("1 - x1-x2",".5 - x1-x2"), 
+solve.variable=c("x1","x2"), jump.coeff=Lambda, measure.type="code",
+measure=list(df="rNIG(z, alpha, beta, delta0, mu, Lambda)"))
+# Look at the model structure by
+str(mod5)
+
+# Ex 6. (Process with fractional Gaussian noise)
 # dYt = 3*Yt*dt + dWt^h
-mod4 <- setModel(drift="3*y", diffusion=1, hurst=0.3, solve.variable=c("y"))
+mod6 <- setModel(drift="3*y", diffusion=1, hurst=0.3, solve.variable=c("y"))
 # Look at the model structure by
-str(mod4)
+str(mod6)
 }
 \keyword{ts}
 
-