About Garnett

Garnett · ‎09-24-2018

Hi, If I understand the question correctly, your data doesn't have an explicit ClusterXRegion indicator. I would create a ClusterXRegion variable in a datastep, e.g. ClusterXRegion = compress(put(cluster,best.) || "_" || put(region,best.)); then replace random delta ~ normal (0, var = S2d) subject = cluster; with random delta ~ normal (0, var = S2d) subject = clusterXRegion;

Garnett · ‎09-24-2018

Greetings! I can write within PROC TEMPLATE: layout overlay / yaxisopts=(label = "p((*ESC*){unicode theta})") ; I'd like the symbol theta (and only theta) to appear in italics. How can I do this? v9.4 Thanks very much in advance! Garnett

Garnett · ‎05-24-2018

That's it! I'm more or less a novice at IML, and really need a better understanding of subscript reduction operators. Thanks!

Garnett · ‎05-24-2018

Sorry about the emoji, I meant to write < : >

Garnett · ‎05-24-2018

Thanks, Rick! It looks like the default behavior of <:> where there are 'ties' across columns is to index the first column in which the value appears. Is that correct? If so, it's just what I need. Also, the approach you give identifies a value of 1 for the row where none of the columns meet criterion. I can work with this, but it will be difficult to distinguish the rows where the first column is truly the first appearance of the criterion, as opposed to rows where none of the columns meet criterion. Thanks again!

Garnett · ‎05-24-2018

Greetings! I have a n x p matrix of probabilities called Z. I'd like to identify the first column within each row of Z where the element < 0.1. These column subscripts will be output to a n x 1 vector called R composed of the column number from Z meeting the criterion within each row. If the criterion is not met within a row, then insert a 0 for that row. example: Z = {0.2 0.3 0.05, 0.01 0.01 0.01, 0.2 0.3 0.5} R={3,1,0} I can think of do-loop approaches, but Z is potentially very large (millions) and I would like a vectorized solution. The origin of this problem is Bayesian sample size analysis for sequential updating, as in http://www.fharrell.com/post/bayes-seq/ Thanks in advance! Garnett

Garnett · ‎03-03-2016

I ran ten chains with uniform(0,0.0001) randomly select stepsize and nsteps random uniform(1,100). The only chains that moved at all had step sizes less than 0.002. These chains explored the posterior, but barely. Convergence diagnostics were far from acceptable after 10,000 iterations. Still no luck using HMC for complex models. Default metropolis sampling works much better for these problem, and, for those problems where I can get HMC to work, the default sampler works just fine. Please share any experiences that you have with HMC!

Garnett · ‎03-02-2016

What experiences have folks had with ALG = HMC(stepsize=<> nsteps=<>) in PROC MCMC? In my experience, I can only get it to work with trivial problems that are just as easily run using metropolis-hastings. For example, I am fitting a hierarchical logistic regression model, and using HMC yields posteriors that are completely immobile unless the step size is extremely small (e.g. stepsize = 0.0001). Even then the posterior samples are highly localized, as one might expect. (I get convergence using the default sampler, but it takes a while and I'd rather speed things up.) Any thoughts or general advice on setting the tuning parameters for Hamiltonian Monte Carlo?

Garnett · ‎08-23-2013

Thanks. I have the red book. I also only have IML 9.3, so clearly I'm getting behind. The Genz and Bretz reference was from one of your posts in this forum regarding MVN tail probabilities. I've also worked from some of the papers Genz has on his website: www.math.wsu.edu/faculty/genz/homepage. In general, my problem is to find points on the surface X such that F(X<= x) = 0.1. For my particular clinical application, I can tolerate a small amount of inaccuracy in those points. It's easy enough to find the curve in 2D using the fcmp solve function for the toy example that I provided (and a small number of applications that I work on). I'd like to develop the method for an arbitrary dimension. Since I have an older version of IML, I will work with the bisection approach that you described. Thanks very much for your insights!

Garnett · ‎08-22-2013

Hi Rick, Thanks for your reply (Love your book, BTW). I am, in fact, looking for contours on the cdf, per your Do Loop post. Here is a greatly simplified example. I would like to do this in IML, but instead of the ProbBnrm function, I'd like to try the multivariate normal cdf module developed by Author : ALAN GENZ and FRANK BRETZ. To do this, I believe that I'll have to code the procedure in IML. proc fcmp outlib = work.funcs.math; function Intersection(_y, _x); return(ProbBnrm(_x,_y,0.5)); endsub; function SolveIntersect(_Perc,_x); array solveopts[5] initial abconv relconv maxiter solvstat (.4 .001 1.0e-6 10000); y = solve("Intersection",solveopts, _Perc,.,_x); return(y); endsub; options cmplib=work.funcs; run; quit; data Solved; do x = -1 to 1 by 0.5; Intersection10 = SolveIntersect(0.1,x); output; end; run;

Garnett · ‎08-22-2013

Hi, I've used PROC FCMP to solve the following problem: Find x such that PRBBNRM(x, -0.2, 0.5) = 0.1. What is the analogous solution in IML? Thanks in advance!

Garnett · ‎08-24-2011

Many thanks for your help. I made your suggested change and reduced the height/width to 2x4inches. I still don't get the correct output when KEYLEGEND is included....

Garnett · ‎08-24-2011

Interesting! I use 9.3....

Garnett · ‎08-24-2011

I get some strange behavior when using 'ods pdf columns=2' approach to generating two columns of plots with sgplot. The problem lies with the keylegend option in sgplot. I want to generate six plots: plots1-4 in the left column and plots 5-6 in the right column. Consider the following example. The program behaves properly when the 'keylegend' statement is commented out. However, if the 'keylegend' is used, then the right columns disappear. This has nothing to do with the location = option. The option can be omitted (so that an empty keylegend appears in the code) and the right column still vanishes. %macro plt; %do i = 1 %to 6; %if i = 5 %then %do; ods pdf startpage = now; %end; ods graphics on / reset = all height = 3.75 in width = 7 in noborder ; proc sgplot data = d1; series x = x y = y / group = g; %*KEYLEGEND / LOCATION = INSIDE ; inset "Plot&i."; run; ods graphics off; %end; %mend plt; **** Play Data ****; data d1; do g = 1,2; do x = 1 to 10; y=x+g; output; end; end; run; options orientation=portrait pageno = 1 ; ods pdf file = "c:\TEST &SYSDATE..pdf" startpage = never ; ods pdf columns = 2; ods pdf startpage = now; %plt; ods pdf close;

Garnett · ‎09-23-2010

Hi Art, Thanks for your interest. I read somewhere that .wav are binary file formats, so that I run data test; infile "c:\...\sample_sfoae.wav" lrecl = 2000; input _x pib5. ; run; proc print output: _x 121438095698 834918219026 I wonder what that means?

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