Hi everyone,
I now have a nitrate time series and I have decomposed it with an additive model, which is Y=T+S+R. I hope to find the best-fit AR(p) model for my residuals. I read from some papers that Mann-Wald process could be used. It would be really great if someone could provide a code on how to find the p. Below is my nitrate residuals. Thanks!
0.160157983184890 2.17307720054057 1.52955989565626 1.45006890417194 2.45078566444762 1.82790551974331 2.69034445775899 4.42816184597468 2.34540928553036 2.68279049780604 1.62871903928173 0.508296837837410 -1.62288362596995 1.00584965715162 -0.543055573966803 0.444003915314771 1.52210606035635 2.59531316141792 2.23891089519949 3.05301642518107 3.10129331550264 0.429833321544216 -0.483079342214210 0.722657253107364 -2.30055733593411 -1.25196701104664 -1.31637009539918 -0.531355848351714 0.193111664455751 1.34662635028322 1.17338288183068 1.38414720557814 0.521082891665609 -0.939218305526926 0.469027827480539 3.37592322056800 2.33001561329242 3.25061121894578 1.20307030535913 1.16590066017249 1.22124884474584 0.251845091339198 1.67106041465255 1.28918353716591 1.18477801701926 0.0406356165926184 -0.0849594546340268 -1.09190526778067 -2.24995407529036 -2.44871656287112 -1.47128179369187 -0.438992641112626 0.582514336226620 1.16346937958587 1.01304349966511 0.941625416944357 1.37737869456360 -0.790604913097152 -0.566041187557907 -0.880828206938661 -2.85271821768246 -2.62150501849733 -2.32172834455219 -1.72158039620705 -1.13491462210192 2.23399921602322 -0.185267868131646 0.230972844913491 0.841384917298627 -1.66993989159624 -2.26121737129110 -2.65584559490597 -3.72157680988388 -3.18420481493285 -1.57576934422182 -1.59696260111080 -0.875138030239769 -1.32156539734874 -0.119673685737717 0.327725823073310 0.0342966932243356 -0.746369320904637 -2.41098800583361 -3.41195743268258 -3.19052985189460 -3.45549906417769 -2.47420479670077 -2.27343925682385 -1.84095589118694 -0.720724461530018 -0.385173953153102 -0.0366156505761843 -0.184385984659268 -1.31839320302235 -0.627853090185433 -1.23616372126852 0.594922655285354 0.629612240768162 0.680365300010968 0.0264896376537763 -1.57986819994342 -1.29947797852061 -0.541768674377802 -0.0945515750349948 0.341836886647812 -0.419011535949380 -0.965312627346572 -1.65496446266376 -2.05971929034400 -1.59887091009531 -2.04045905108661 -1.84717592067791 -0.914874961509212 -0.226825944320514 1.11411769358818 0.0414180536968818 0.403965307145579 -1.19572431668572 -1.37686661331702 -2.79685965286833 -2.17045568678267 -2.08344851076809 -1.18137785499350 0.230564069181090 0.881023826115679 0.0227316420702668 -0.530741462255145 -0.357706770380556 0.0349992798340315 -0.698531551231380 -1.05651505209679 -4.02404929588220 -2.89478653203066 -2.49912055925018 -2.47739111070970 -1.41929038776922 -0.575671836068746 -0.598305226348267 0.251380466092211 1.14757395173269 -0.00256120028683160 -1.54793323558635 -1.95875793968587 -4.12723338970539 -2.33071182708796 -1.53588705954159 -0.795498819235224 -0.171239299528854 1.98353804593751 0.109563456423885 -0.767092058369746 0.577760226036623 0.131283870782992 -0.430929367750639 -0.290095279084269 0.705388069662101 1.21076842304542 -0.961248012642317 -1.03140097157006 -0.115282656097797 -1.94334651886554 -0.838662314613278 -1.00965903164102 -0.513147954468758 -0.0424655139564996 -1.40851995472424 -1.22502706929198 0.586615073220280 2.16315422436950 1.62729658344764 0.212002419285794 1.55057952852394 -0.763825535477906 0.377017466540245 0.0813795432783944 0.639249419216544 -0.193509344505306 2.11279500549285 2.01474669169100 -1.00665237203085 0.375245576884251 0.344746729728291 0.435311359332332 -0.988452728663628 0.0468009991004125 0.0158027948844535 1.18002366838849 0.519252337092534 0.898752374136574 0.100515518900615 -0.281874001135344 0.713085731908695 -1.09165752441031 -2.17499757480038 -2.10387414943045 -1.77597944666052 -0.335066915130585 -0.670506325580654 0.393873344689276 -0.213639190840792 -0.828080362030862 -1.39885841850093 -1.82138914777100 -2.41957061596107 1.72474492348582 0.637563669861638 0.321345894997459 -0.755900606466719 -2.14292928117090 -2.80640989885508 -1.73387142881925 -1.20402517258343 -0.536207547007612 -1.73462680671179 -2.56629873921597 -3.79432141264014 -2.94124707742737 -1.04946953428566 -0.898328514383944 0.774783777917767 3.60581389697948 2.61549207606119 2.76878934386290 -0.744105601135384 0.0338708192063266 1.60881035226804 1.63889721452975 1.09333333887146 1.23066646885013 0.306902806757731 0.514602623425335 0.356773715492936 -1.77063737567946 -1.12520039783186 -2.26704433826426 -2.17208048749665 -0.219945266389052 0.984453062438551 4.21439872146615 10.6309936395738 9.58348556531831 4.84058069899181 3.25023931042530 2.76976919525879 1.30981690685228 1.62141267746578 1.80372752879927 1.38985018133276 2.03514418820625 1.38900131579975 -0.0668942244067584 0.495559489466734 -0.124789789022819 0.229564143416563 0.229581547615947 0.273870225215330 1.82887673657471 1.85863130295410 1.18370495705348 0.587686401352863 1.44833920699225 0.397255127351630 0.528218379911014 3.31003088855040 3.85584040582673 3.65225313103201 2.73822933399728 1.88907681036256 1.00744211748783 2.54305547663310 1.16348792049838 0.774428165563654 -0.157960233031073 -0.634385520905799 -0.874163468580525 -0.621292162175251 -0.0626238501330239 0.257947670838141 -0.280817329430694 -0.193811057299531 -0.206486957408366 0.0863852015027977 -0.881223561866039 -0.774924524034874 0.828845879136291 1.08787938602746 -1.24653976888138 -1.39630966371022 -2.43148255990210 -1.19245223716504 -0.186158441667991 2.20900662222907 1.73238951688612 0.953620476563174 2.39637050596023 1.36212834255728 1.19055753649434 1.99474984415139 0.524489482008449 -0.385121619054498 0.361164285519512 -0.610946599977543 -0.0421940147145987 -0.0471701500516536 -0.456328459628708 -0.816938703185762 -0.231329876022817 0.558086756340128 0.347174743043072 4.07052584846602 2.45642428408896 2.17897197679191 0.563416677131806 1.06146458540064 -0.415624030570522 -0.318141367141684 -0.259940878952849 1.61980766225599 0.778375292184820 -0.00854928268634358 0.530197499782492 -0.00279259602867288 0.940064630360165 3.74897112182900 3.04957461793479 2.30278132196951 1.40255150376424 1.38919295895897 0.0974522399136985 0.133559588888423 0.612486007583148 -1.31357977552212 0.332425808712600 -0.741205491332674 1.26801053182205 2.64687581605678 1.38863810792846 1.73500360772908 0.906932585289691 0.0380328362503098 0.0930509169709258 0.471917055711543 0.832802270172159 0.327095283832775 0.200359660833392 -0.307012841445991 -0.207738021525375 2.98568605947524 2.52960714711281 2.30613144267932 1.43821921600583 4.66417826273233 2.41865513621884 1.17408007572535 -0.968475910048146 -1.06672410162164 0.435699070144867 -0.679114644368625 1.52121897631788 1.66340185208439 1.10648173548785 0.756164826820247 1.72841139591265 2.79052923840504 1.06346490465744 -0.0409513640701629 -0.386648549077766 -1.06953794088537 -0.520855978352972 1.45028910589943 1.25068152235183 -0.195976806115778 -1.33073812694643 -0.110896239848139 0.792509125010148 0.900885761268438 0.0725802262867249 -0.498077241674988 -1.13091563691670 -1.05444623295841 -0.307505475660124 -1.27820159064184 -1.73985038542355 -0.0304499151252560 -5.12133439419001 -4.62070827832584 -3.96203870770166 -2.67526216267748 -1.57287548189330 -2.88789757708912 -1.62167717956495 -2.11834897984077 -1.28414942177659 -1.70968674699241 4.62332326199177 -1.62001747194405 1.76553879575708 0.946698274387148 0.0514212307772164 -1.44598453843271 -3.22087248488264 -2.62551236631258 -1.79483316802251 -2.78364617353244 -3.25328781670237 -2.00766635015230 -3.04849754640223 -4.02067948957216 2.85603558089486 3.67835385529082 3.55423560744678 -0.964816690997261 -0.0707405176813029 -1.95922160334534 -1.69738360428939 -1.88503782003342 -1.86352066543747 -0.426740398121506 -0.926412799605548 -1.16743594600959 4.46043791522332 0.513914985385175 -0.609044463692976 0.635867352628874 -1.54670300128928 -1.04902528518743 -1.43602850036557 0.0674760866562765 0.630152029018126 -0.636908900900024 0.0995774943818254 0.0697131407436751 -1.49125420025752 0.793381664670220 0.451581008357960 -3.26734837355430 0.556240070293440 0.611776578161180 -0.970767841251080 0.0538955415366611 -0.587269719335599 -0.663171856487859 0.0461733355598827 -1.80923222131238 -2.01404076954768 0.436753893145947 -0.153887963400423 -0.146658553546792 -0.966911317933161 -0.326916009299530 -0.841601633945901 -1.88577945139227 -0.590785914498639 1.08947074111499 1.08327472192862 -1.99427203217775 0.702078213352839 0.161031670812359 -0.305451395968119 -0.0870631873485989 -1.05615714796908 -0.165003055569557 -0.773529877450035 -2.27154890113051 -1.13039657147099 -0.903981119091473 -1.86901833951195 1.79459369914757 2.51410274444404 1.16521499766946 0.926890728654869 0.286437729040281 -0.598197438814308 -2.16248454264890 -0.796552569763486 -1.39341280067807 -1.80610167425266 -2.10682742810725 -2.98740584776184 -3.87424976333643 0.251032824725939 -0.286696126282760 2.52313840046854 -0.832855802380152 -1.04293216946885 -1.20446048253755 -1.24396971188625 -2.56137115303494 -2.79960122284364 -2.93416817993234 -2.09188780882104 4.93404181737026 6.02886845419852 1.95429829895571 0.760291621472907 0.411885251390097 0.264538642067290 0.607469126764484 0.604118691181675 -0.442123951201132 -0.900795234243940 4.35409660743325 4.04753577531044 0.174624200267637 -0.994390369138215 0.962198273384867 -0.532649610332050 0.390373785351033 -0.889085000205883 0.621704283257200 -0.382187354559718 -0.182271203176635 -0.624783684453552 0.571266947989530 0.0875649126326145 -1.81088786764430 0.836256360715734 0.439003797004706 0.755314711053681 0.484496895502654 -0.453803086288373 0.753144987940602 -0.524587859110426 -1.03181290496145 -0.819866594472480 -0.122657165263506 0.528099596145467 -1.38249438836556 -0.704191361239631 -0.470285127184769 -2.24286389536990 -0.0924744411550401 0.920384369819825 -0.961508756185312 -0.978082804470449 -0.264149055555584 0.188956052699280 -1.13267572632586 -0.310760169150993 -1.35019535689613 -1.99073353500431 -2.53566850718355 -1.48704000260280 -0.860540224622045 -0.981522618881289 -0.0122569541205351 -0.437672201639781 2.75959194904097 -0.798315758938272 5.35121126480248 3.64428561574324 0.276009223763989 -4.23121581557830 -0.717146338991657 -0.867359035645010 -0.709700457898366 -0.819524061391721 -1.57909959586508 -1.10335605361843 1.53743933782821 -1.46168201238514 -2.03099619687850 -2.43676305417185 4.07611935261479 -2.98386917296161 -2.14885749960907 1.67622748050346 0.415044854015996 2.85138005228853 -0.722036694418932 0.0648656475936020 -1.11772421519386 1.62089454035867 -1.06929811336879 1.87109382810374 0.750135030656278 0.113073237845765 -1.77166313103581 1.54871954584262 -0.484093911878955 1.32618970415947 0.273931763217895 2.47184567199632 0.745561821974748 -0.436697879706828 1.03975741733160 0.582856264570025 0.328056260888449 1.15215326084383 1.16185347172814 1.68511716037246 0.213760721416778 -0.0100950887789047 0.728805765045413 -0.746974307410273 3.81753391533404 0.311652508418360 2.93081470622268 0.713524247226995 2.98988303431131

 Akzeptierte Antwort

Roger Wohlwend
Roger Wohlwend am 24 Jul. 2015

0 Stimmen

You could use the Akaike or the Bayesian Information criterion (Matlab function aicbic). Also consult the page "Choosing ARMA lags using BIC" in the Matlab documentation.
A less sophisticated way is to try different values for p, estimate the model in each case and choose the p where the model's residual are free of autocorrelation.
The Matlab function parcorr suggests that the optimal value for p is 1 in your case. Indeed, for p = 1 the model seem to be quite good. The residuals are free of autocorrelation, the R-square is 0.35 and the coefficient is significant.

1 Kommentar

xiaoli su
xiaoli su am 24 Jul. 2015
Thanks Roger, I have tried the BIC before and it showed the best model ARMA model. However, when I was using autocorr, I got a ACF graph which has a quite significant value at lag 12. I wonder if this is related to the p of AR model or what it indicates.

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (0)

Kategorien

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by