Calculate residuals from a stackedsdm object
residuals.stackedsdm.RdCalculate residuals from a stackedsdm object
Usage
# S3 method for stackedsdm
residuals(object, type = "dunnsmyth", seed = NULL, ...)Arguments
- object
An object of class
stackedsdm;- type
Determined what type of residuals to calculate. The current options include Dunn-Smyth residuals (default; "dunnsmyth"), raw response residuals ("response") or probability integral transform residuals ("PIT");
- seed
For Dunn-Smyth and PIT residuals applied to discrete responses, random jittering is added, and the seed can be used to seed to jittering.
- ...
not used
Examples
X <- spider$x
abund <- spider$abund
# Example 1: Simple example
myfamily <- "negative.binomial"
# Example 1: Funkier example where Species are assumed to have different distributions
# Fit models including all covariates are linear terms, but exclude for bare sand
fit0 <- stackedsdm(abund, formula_X = ~. -bare.sand, data = X, family = myfamily, ncores=2)
residuals(fit0)
#> Alopacce Alopcune Alopfabr Arctlute Arctperi Auloalbi
#> units1 0.84676395 0.90113447 -0.60660144 0.15442680 -0.6311492 -0.62360740
#> units2 -0.80591386 -0.90472309 0.28382635 -1.09652669 2.7051703 -0.79258430
#> units3 0.53716968 1.25368356 0.73320080 1.51361387 -0.3309628 -0.15235196
#> units4 -1.56962127 0.18754882 -2.58323935 0.31953099 1.1630902 1.45042873
#> units5 -0.70007835 0.98237346 0.45162688 0.40049171 -1.6871373 0.23480007
#> units6 -0.60162141 0.08204508 -0.21648113 1.25389243 0.7615577 1.34188517
#> units7 0.36801414 -0.16992164 -0.03210456 1.07116900 -1.0861311 1.11917089
#> units8 -0.93997030 1.60616294 1.19209686 0.52261975 0.3880035 0.83515524
#> units9 -1.43981252 -0.49724220 -0.78355308 0.17591727 0.8650652 -0.50575128
#> units10 -0.82210122 -0.59294303 -0.25549161 -0.79428348 -0.3915386 0.25838852
#> units11 0.83029558 -0.27992850 0.33738096 -1.21552115 -0.5308967 1.06606521
#> units12 0.74126066 1.87958212 -1.65682064 -0.64846500 0.4267813 -0.74845115
#> units13 0.66189067 0.19097304 1.37202293 -0.82095276 -0.1155773 -0.08102301
#> units14 -0.12428711 -0.49407052 -0.43014544 -1.14900037 -0.6078006 -1.71908761
#> units15 -1.42665142 -1.62556832 1.47471821 -1.84034112 1.6192901 -0.97799988
#> units16 0.03836433 1.28028221 0.52346124 0.17898767 0.1903424 0.28472672
#> units17 0.61470968 -1.49254594 1.06649342 0.94987251 1.1452556 -1.84668864
#> units18 -2.99553019 -1.04457821 -0.30727629 0.60683392 0.1854106 -1.52041432
#> units19 1.47588554 0.23312224 -1.21051746 1.14777232 -0.1881938 -0.39372275
#> units20 0.46196853 0.89344266 0.12023512 -0.51104778 -0.6398224 -0.21288709
#> units21 0.99266321 0.16923131 0.30186560 -0.04853513 -0.2052426 0.21825730
#> units22 1.74921496 -0.71209329 0.61017559 -1.84854001 -0.3371181 0.47840319
#> units23 -0.66530306 -0.66986003 0.22765969 -1.07468897 -0.5993605 -1.37092530
#> units24 -0.18159553 -1.07773200 1.88618062 -0.94346708 1.3202356 -0.39004366
#> units25 1.77367701 0.43308449 1.48175391 0.68294069 0.3186063 0.26741492
#> units26 -1.29591520 0.14531344 -1.44386296 -0.83607019 0.1531407 0.36723046
#> units27 0.66102149 -1.03575240 -0.35697241 -0.22932974 0.9881757 -0.22635542
#> units28 -0.80409719 -0.72226129 -0.16656504 -0.54452761 -0.3709130 0.75625524
#> Pardlugu Pardmont Pardnigr Pardpull Trocterr
#> units1 -0.15529979 0.61162906 1.388567774 1.580238645 2.43554057
#> units2 -0.74059598 -1.56539604 -0.394992875 -1.065985150 -0.33452021
#> units3 1.32450281 -0.14625283 0.847925882 0.147322828 1.50602885
#> units4 0.99418481 -1.41388288 0.715584584 0.748173860 1.45524225
#> units5 0.05696165 -0.98776657 0.663419641 1.305130860 -0.46411210
#> units6 -2.46656211 0.79082736 1.509057535 1.509600172 0.34794234
#> units7 0.67644082 0.88177118 0.001694762 0.241591034 -0.17404911
#> units8 1.73334998 1.14886093 0.749165801 0.836116548 0.61702647
#> units9 1.05510660 -0.49303435 -0.225385269 -0.296598391 -1.64092213
#> units10 -1.28544027 0.72152031 -0.089990886 -0.625627849 -1.62939799
#> units11 0.16008074 1.26199170 -0.348386039 -1.207344511 -0.91321762
#> units12 0.09982693 1.07779068 -0.347851496 -0.008974913 0.18519985
#> units13 1.42321372 0.81342008 0.588209944 -0.783199881 -0.27820064
#> units14 0.83218978 -0.62361557 -1.370200529 -1.203454186 -0.27737316
#> units15 -0.30531527 -1.96310455 -1.525919763 -0.914965315 -0.85293974
#> units16 -0.34609385 1.26191171 2.160604304 0.379924008 1.34661108
#> units17 -0.76133229 -1.81839424 -1.212556216 -1.046400861 -0.95727795
#> units18 -0.59152347 -0.04500548 -0.858840601 -0.783645808 -0.69396322
#> units19 0.14857238 -2.76876012 1.088228690 -0.994971191 0.78600749
#> units20 1.24765086 0.02444553 -0.031964786 -0.656284892 0.66770767
#> units21 0.06174067 1.22370247 0.126814017 2.586227799 -0.13931405
#> units22 -0.96333122 0.58206577 -0.330051706 0.701922779 1.02603911
#> units23 2.03192490 -0.22853509 -0.525335452 1.005356980 -0.08017796
#> units24 -0.53459813 -1.19476455 0.260915924 0.451479704 -1.95271802
#> units25 -1.28505093 1.90803762 0.964923910 -0.311800427 0.15784024
#> units26 -0.21827439 -0.51633915 -0.061548333 -1.734712297 0.45113334
#> units27 -0.84923222 -1.07313568 -0.433837627 1.265191408 -2.34110636
#> units28 -0.72362752 0.31798783 0.935715456 1.661593609 0.68401794
#> Zoraspin
#> units1 1.20270292
#> units2 -0.64381557
#> units3 -0.68176021
#> units4 1.93188045
#> units5 -0.32977002
#> units6 1.29676287
#> units7 -0.59755860
#> units8 0.32678568
#> units9 -0.93120131
#> units10 -0.01442898
#> units11 -1.69465063
#> units12 -0.96918643
#> units13 1.20027315
#> units14 -0.61093435
#> units15 -0.46768975
#> units16 1.16411525
#> units17 -0.53751792
#> units18 -2.28768233
#> units19 0.42576996
#> units20 0.50473153
#> units21 -0.01702470
#> units22 -1.33452255
#> units23 -0.07235338
#> units24 0.53606500
#> units25 1.29568163
#> units26 -0.64525976
#> units27 -0.25685202
#> units28 0.31167168
# Example 2: Funkier example where Species are assumed to have different distributions
abund[,1:3] <- (abund[,1:3]>0)*1 # First three columns for presence absence
myfamily <- c(rep(c("binomial"), 3),
rep(c("negative.binomial"), (ncol(abund)-3)))
fit0 <- stackedsdm(abund, formula_X = ~ bare.sand, data = X, family = myfamily, ncores=2)
residuals(fit0)
#> Alopacce Alopcune Alopfabr Arctlute Arctperi
#> units1 1.092284826 0.17215280 -1.28437483 -1.671999373 0.69875790
#> units2 -1.765234638 -1.20957574 0.23761368 -0.369366852 0.05653940
#> units3 1.172792414 -0.66632813 1.46957671 0.921227361 0.67599721
#> units4 1.025075066 -1.26402183 -0.93140561 0.603600093 1.49302548
#> units5 2.416192603 0.28867107 -0.18740381 0.966922153 0.71904378
#> units6 -2.332430782 1.26854437 -1.46990497 2.077890590 -2.79520233
#> units7 0.547025681 -1.07429026 -1.31411328 2.068926515 1.18046291
#> units8 -1.784682057 -0.45589944 0.85432398 -0.580803966 -1.23653684
#> units9 0.164067610 0.78412837 -1.04650524 0.197864574 0.04533819
#> units10 -0.119758270 1.06168194 1.29736494 0.258358131 -1.45416278
#> units11 0.996861080 -0.04575339 1.51832978 -0.842509217 -0.68458393
#> units12 0.775420808 -0.93683514 -0.87625862 -0.121790967 0.44264081
#> units13 1.128804658 0.18127252 0.81392701 1.262413035 -0.66889709
#> units14 -0.124847791 0.79314749 -1.40767628 0.795600423 -1.36509529
#> units15 0.006266484 -1.33860105 -0.04661852 -0.168995469 1.22306377
#> units16 -1.271087026 -0.79608516 -0.03849232 0.006541949 0.30341108
#> units17 -1.625953413 -1.51751182 0.64329162 0.376468065 -0.56925213
#> units18 -1.172542830 0.86286196 -1.04877709 -0.507414789 -0.13451888
#> units19 -1.699116975 1.09322224 -1.59653761 -0.196095369 0.09123978
#> units20 -0.522534418 -0.07828422 1.00376420 -0.177512524 -1.18613673
#> units21 -0.257354192 0.88847912 0.24822430 -0.373885890 0.96309522
#> units22 0.328581076 -0.21365139 -0.96830754 -0.953173481 0.60494435
#> units23 -0.523151994 0.31521957 -0.61987914 -1.118210641 1.33489289
#> units24 -0.068986012 -0.52856140 0.82202143 -0.123824562 0.73910941
#> units25 0.280665820 1.56337339 0.49754263 0.676170607 -0.78115784
#> units26 0.219524843 -1.24428276 0.17704969 -1.162720842 0.33440117
#> units27 0.312785045 -1.43798238 0.65374666 0.656910994 1.66985327
#> units28 -0.055549347 0.23784659 -0.36074712 0.650662452 -0.14578664
#> Auloalbi Pardlugu Pardmont Pardnigr Pardpull Trocterr
#> units1 0.49127046 -1.12612323 1.30497694 0.51096600 0.84054776 0.47778733
#> units2 1.49732483 -0.44918225 -0.56557818 0.58700684 0.76884435 0.58594724
#> units3 0.81213275 -0.25859775 0.76654498 0.64915513 0.84464145 0.60350197
#> units4 1.35242610 -0.49950495 0.01986302 0.84955625 1.17756006 0.86165169
#> units5 0.81824607 -0.41762853 -0.36547825 1.75754146 1.07629490 0.91222296
#> units6 1.29133838 -0.30247578 0.60701039 1.56834752 1.63573704 2.04254333
#> units7 1.09501408 -0.38123293 0.79432699 1.45132810 1.23655651 1.19417230
#> units8 0.67975073 2.53515362 -0.47115406 -0.04816686 -0.20263645 -0.02497191
#> units9 -1.92836621 -1.48650473 0.70273527 -0.12895532 -0.22233778 -1.31328640
#> units10 -0.99348909 -0.43515886 1.37748022 0.11161866 -0.64954335 -0.75788900
#> units11 -0.06176787 -1.55919723 1.72711102 -0.38938276 -0.20006212 -1.13464700
#> units12 -0.35076601 -1.37610295 1.74177471 -0.09313934 0.29193461 -0.53674211
#> units13 1.90432874 0.11940141 0.97174216 1.82835460 2.07720649 2.21385171
#> units14 0.48990912 0.07024112 0.34198442 0.58123597 1.04745497 0.94398161
#> units15 -0.22878656 0.38599624 -1.99160333 -0.75934096 -1.12569336 -0.16625665
#> units16 -0.65217256 0.38465635 -0.96390392 -0.04240769 -0.35971676 -0.07257776
#> units17 -1.10798772 -0.07742627 -0.88310474 -0.87566189 -0.79095181 -0.20335296
#> units18 -0.36774508 0.29410941 -0.78672102 -1.25581276 -0.72374283 -0.16220929
#> units19 -0.99276713 0.87026225 -2.72840600 -0.08009601 -0.88900939 -0.24582606
#> units20 -0.26986761 0.95430690 -1.49959411 -0.89943040 -0.47669033 -0.23525012
#> units21 -0.53075442 1.15105825 -0.66476459 -1.54830204 -0.10512698 -0.35476091
#> units22 -0.19486808 -0.64727475 -0.01511828 -1.34934917 0.04050169 -0.85721580
#> units23 0.13708151 1.62413699 0.39499647 -1.13502808 -0.49005951 -0.94663692
#> units24 -0.93182081 0.15830051 0.02679960 0.14343189 0.16318302 -1.69848073
#> units25 0.94264656 1.10688792 0.81905196 1.09237823 0.04805092 1.11365184
#> units26 0.30572810 1.05612874 -0.66283818 0.01427232 -0.35272909 -0.57938222
#> units27 -0.87868845 -0.88307732 -0.52378449 -0.57650169 -1.49910055 -1.57885345
#> units28 -0.91058381 0.19943272 0.44461105 -2.12411278 -1.87464444 -0.58485384
#> Zoraspin
#> units1 0.19559296
#> units2 0.59393381
#> units3 -0.23305194
#> units4 1.29502986
#> units5 1.01072224
#> units6 2.12284707
#> units7 0.95432447
#> units8 0.15845410
#> units9 -0.66586490
#> units10 -0.40394091
#> units11 -2.09683663
#> units12 -2.19871410
#> units13 1.55191200
#> units14 1.51443809
#> units15 0.06338783
#> units16 0.27912554
#> units17 -0.03646092
#> units18 -0.75771886
#> units19 0.07209813
#> units20 -0.09335670
#> units21 0.02334781
#> units22 -0.79562413
#> units23 -2.13032299
#> units24 -1.03292910
#> units25 0.91824403
#> units26 -0.62995488
#> units27 -0.63008756
#> units28 -0.19985497