r_vitals.RdDraws values from a random uniform distribution (see function runif() ) between a minmum and maximum value.
r_vitals(d = 0.25, n = 10000, params. = param_set())
| d | sets range of data to draw random values from (delta) |
|---|---|
| n | number of simulated life histories |
| params. | starting values for parameters. Defaults to output of param_set() |
px2 xxx
TODO: split this up into sep function 1st, generate random valueas 2nd, make sure high quality > low quaity 3rd, contstain to a particular lambda value output diagnostic plots to examine be able to set lambda values from function (current hard coded) be able to allow any lambda values allow tolerances to be set on lambda values being used as references (currently use round() as a clunky way to make this work)
random.vitals <-r_vitals() head(random.vitals) #> S.w.fg S.w.fp S.m.fg S.m.fp S.b.fc S.b.fk S.f.fc #> 1873 0.7543400 0.7003431 0.9773236 0.9736435 0.9961088 0.8325422 0.7197066 #> 3185 0.7389030 0.7258221 0.9342319 0.8392916 0.7788868 0.7719384 0.9889531 #> 3415 0.8208713 0.7770452 0.7692821 0.7398411 0.8934320 0.8037966 0.7845557 #> 4255 0.8273149 0.7973646 0.8733134 0.7599667 0.8452933 0.8328583 0.9925424 #> 5745 0.9030721 0.8972997 0.8455739 0.7332654 0.9433235 0.8297175 0.8642536 #> 5881 0.9277549 0.8514534 0.7619092 0.6951580 0.7508966 0.6735178 0.8832557 #> S.f.fk S.y.fc S.y.fk R.base.rate R.hab.effect f S.ad.hi #> 1873 0.7114239 0.9173880 0.8712749 1.831127 0.4501040 0.5 0.5285277 #> 3185 0.8128288 0.9445320 0.7671436 1.711873 0.6204255 0.5 0.5317312 #> 3415 0.7142379 0.9661392 0.7831177 2.040444 0.5849981 0.5 0.4426352 #> 4255 0.7627583 0.8236380 0.7278495 1.707757 0.5839341 0.5 0.6061743 #> 5745 0.8478304 0.7429496 0.6204812 1.529647 0.3987078 0.5 0.6225523 #> 5881 0.8420214 0.8340811 0.6373344 2.165886 0.5401717 0.5 0.4688167 #> S.juv.hi Fec.hi Lamb.hi S.ad.lo S.juv.lo Fec.lo Lamb.lo #> 1873 0.6763299 1.831127 1.147751 0.4038737 0.5941088 0.8241977 0.6487052 #> 3185 0.6520168 1.711873 1.089816 0.3822301 0.4673258 1.0620898 0.6304011 #> 3415 0.6100991 2.040444 1.065072 0.3300455 0.4502065 1.1936559 0.5987413 #> 4255 0.5950828 1.707757 1.114303 0.3849547 0.4410554 0.9972174 0.6048688 #> 5745 0.5673268 1.529647 1.056457 0.4628475 0.4082511 0.6098822 0.5873400 #> 5881 0.5895828 2.165886 1.107301 0.3356732 0.3772348 1.1699504 0.5563462