In order to do this, you will have to open the figure editor and “add data” to the figure and select the impulse response from the first simulation that you saved. You can then import your first set of impulse responses into that workspace and add them to your new graphs. Following this, dynare should give you the plots for the impulse responses. Once they are saved, you can then run the simulation again under the alternative scenario. They can be found in the workspace window. One of the things I have done is to run dynare under one “scenario” as you put it, and then save the impulse responses for that scenario. One of the main problems I am having is that I am unable to save the irfs (irf1 and irf2) separately, one keeps replacing the other in my folder. mfcolc (nrows, ncols) fills in the matrix by columns. With the par ( ) function, you can include the option mfrowc (nrows, ncols) to create a matrix of nrows x ncols plots that are filled in by row. Hopefully, this is clear from the attached files. Combining Plots R makes it easy to combine multiple plots into one overall graph, using either the par ( ) or layout ( ) function. So for example, say I have two scenarios, in each of the graphs I would like the irfs from both scenario A and B for each variable. I am trying to generate graphs for the same sets of variables but from different scenarios. I know this topic has been covered but I think the code file I am working with are a bit different. I am trying to generate multiple IRFs on the same graph. You can simplify the code and the graph, if the two categories really are as simple as 'X' and 'Y': xyplot (y x graph, groupsvar, datadat, type'o', pchc ('X', 'Y'), cex1.25, ltyc (2, 3), layoutc (1, 4), as.tableT, xlab'Time (secs)', ylab'Price') which will use 'X' and 'Y' as the point symbols. The mult_irf file was just my initial attempt to start writing a code that would merge the results. You would only need to run the run.m and run.1 files to see the irfs I am trying to merge ( Alternatively, you can stick with running the run file but changing fcI from 0 to 1). I attach the other files you would need in a zip file. I got to this stage because I tried running the single run file twice but under the two different scenarios and saving the simulation results in oo_.endo_simul as irf1 and irf2 respectively but irf2 would just replace irf1 in my folder so I thought I should try to name the files differently, but this doesn’t seem to have worked. I am not sure whether it is necessary to name the files differently. I want to generate irfs for the set of variables in the transition.mod file under these two scenarios in the same graph for each variable. Enter Month and your two Y variables, and make sure Overlay is checked and also. Run refers to the scenario where pmrI = 1 fcI = 0 ubI = 0 while run_1 is set to pmrI = 1 fcI = 1 ubI = 0. Use the Chart platform if you want to make this combined plot manually. As these two files are currently set up, they run the same mod file, under two different names transition.mod and transition_1.mod because I thought this might help. For instance, assuming I wanted to print two plots in grids 1 and 4 using the example code above, all I would have to do is alter the layout function as follows.Run and run_1 have the same code in them but apply to two different scenarios. I find myself working with odd number of plots on an even grid and all I do is tell layout which grids my plots should be drawn in. R graphs support both two dimensional and three-dimensional plots for exploratory data analysis.There are R function like plot(), barplot(), pie() are used. Layout(matrix(c(1, 2, 3, 4), nrow=2, ncol=2, byrow=TRUE))Ĭode for plot 4 goes here R Graphical Representation – 4 Plots on 4 Grids Don’t mind the code for the plots –I deliberately left it out since it’s insignificant in this context. The R code below pretty much prints out four barplots onto one graph, as shown in the proceeding graph. I have in the past also played around with the par() function, but layout() is my favourite □ I find that the R layout() function is a lot easier and more flexible to work with when combing multiple plots into one graph.
0 Comments
Leave a Reply. |