Home » date » 2010 » Dec » 29 »

LOESS 2

*The author of this computation has been verified*
R Software Module: /rwasp_decomposeloess.wasp (opens new window with default values)
Title produced by software: Decomposition by Loess
Date of computation: Wed, 29 Dec 2010 17:29:28 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb.htm/, Retrieved Wed, 29 Dec 2010 18:27:11 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
34420 34070 33978 34484 34645 34410 34534 35019 35508 35488 35709 36534 36066 35724 35727 36281 36017 35780 36003 36285 36419 36413 36663 37451 37063 36613 36564 37064 36817 36621 36798 36967 36926 36975 37324 38159 37776 37465 37451 37944 37737 37603 37813 37960 37934 37975 38241 39176 39137 38797 38730 39031 38851 38727 39291 39407 39326 39326 39617 40458 40425 40092 39939 40174 40065 39922 40107 40163 40116 40118 40416 41215 40852 40497 40430 40766 40626 40442 40590 40673 40660 40736 41082 41873 41507 41104 40963 41227 41063 40873 41016 41433 41345 41375 41597 42225 41937 41642 41551 41866 41744 41615 41764 41828 41786 41852 42183 42937 42635 42292 42202 42577 42600 42433 42584 42660 42659 42712 43039 43664 43397 43110 43005 43159 43066 42977 43139 43226 43242 43348 43605 44225 43983 43754 43632 43868 43864 43808 43954 44032 44090 44210 44435 44919 44785 44616 44 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal21510216
Trend1912
Low-pass1312


Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
13442034522.17504862338.29236736257533979.5325840174102.175048620011
23407034025.5539082102-27.862092065124634142.3081838549-44.4460917898032
33397833830.0438949806-179.12767867305834305.0837836924-147.956105019381
43448434440.996440075361.454331566142634465.5492283585-43.0035599246912
53464534755.2822953253-91.296968349937834626.0146730246110.282295325291
63441034321.8861748901-285.08184265858334783.1956677685-88.1138251098819
73453434308.9344830045-181.3111455167434940.3766625123-225.065516995535
83501935042.9251166396-99.790905255996235094.865788616423.9251166395552
93550835881.5824732657-114.93738798631235249.3549147206373.582473265691
103548835707.5735803652-124.94914141877635393.3755610536219.573580365191
113570935813.620215387866.983577225692735537.3962073866104.620215387753
123653436777.7026039634637.62688832316835652.6705077134243.702603963437
133606636025.7628245972338.29236736257535767.9448080402-40.2371754028063
143572435614.1171744417-27.862092065124635861.7449176234-109.882825558299
153572735677.5826514665-179.12767867305835955.5450272066-49.4173485335486
163628136465.052037636861.454331566142636035.4936307971184.052037636757
173601736009.8547339623-91.296968349937836115.4422343876-7.14526603765262
183578035649.0829837333-285.08184265858336195.9988589253-130.917016266721
193600335910.7556620537-181.3111455167436276.555483463-92.2443379462857
203628536316.9673522978-99.790905255996236352.823552958231.9673522977828
213641936523.8457655329-114.93738798631236429.0916224534104.845765532911
223641336451.6538185386-124.94914141877636499.295322880238.653818538558
233666336689.517399467366.983577225692736569.49902330726.5173994672659
243745137630.2715271432637.62688832316836634.1015845336179.271527143203
253706337089.0034868772338.29236736257536698.704145760226.0034868772054
263661336500.7235080688-27.862092065124636753.1385839963-112.276491931181
273656436499.5546564407-179.12767867305836807.5730222324-64.4453435593314
283706437209.933370057261.454331566142636856.6122983766145.933370057246
293681736819.6453938291-91.296968349937836905.65157452082.6453938291088
303662136564.8890896863-285.08184265858336962.1927529723-56.1109103137278
313679836758.5772140929-181.3111455167437018.7339314238-39.4227859070525
323696736948.3743128541-99.790905255996237085.4165924019-18.6256871459191
333692636814.8381346063-114.93738798631237152.0992533801-111.16186539374
343697536847.2847110483-124.94914141877637227.6644303704-127.715288951651
353732437277.786815413566.983577225692737303.2296073608-46.2131845865006
363815938293.7965480124637.62688832316837386.5765636644134.796548012411
373777637743.7841126694338.29236736257537469.923519968-32.2158873306107
383746537402.3900223928-27.862092065124637555.4720696724-62.6099776072297
393745137440.1070592964-179.12767867305837641.0206193767-10.8929407036121
403794438103.212479804961.454331566142637723.3331886289159.212479804948
413773737759.6512104688-91.296968349937837805.645757881122.6512104688009
423760337597.1280326511-285.08184265858337893.9538100074-5.87196734885947
433781337825.049283383-181.3111455167437982.261862133712.0492833829994
443796037937.6098932905-99.790905255996238082.1810119655-22.390106709543
453793437800.837226189-114.93738798631238182.1001617973-133.162773811026
463797537790.7278628122-124.94914141877638284.2212786065-184.272137187756
473824138028.674027358666.983577225692738386.3423954157-212.325972641425
483917639220.0492179284637.62688832316838494.323893748444.0492179284192
493913739333.4022405563338.29236736257538602.3053920811196.402240556323
503879738902.4271312625-27.862092065124638719.4349608027105.427131262462
513873038802.5631491488-179.12767867305838836.564529524272.5631491488384
523903139050.549653874361.454331566142638949.996014559619.5496538742882
533885138729.869468755-91.296968349937839063.4274995949-121.130531244969
543872738569.8352614009-285.08184265858339169.2465812577-157.164738599131
553929139488.2454825962-181.3111455167439275.0656629205197.245482596227
563940739533.8084219229-99.790905255996239379.982483333126.808421922949
573932639282.0380842407-114.93738798631239484.8993037456-43.9619157592679
583932639189.6772783935-124.94914141877639587.2718630252-136.32272160647
593961739477.372000469466.983577225692739689.6444223049-139.62799953061
604045840499.08123819637.62688832316839779.291873486841.0812381900323
614042540642.7683079687338.29236736257539868.9393246687217.768307968749
624009240269.3534972808-27.862092065124639942.5085947844177.353497280754
633993940041.049813773-179.12767867305840016.0778649001102.049813772996
644017440208.680244315261.454331566142640077.865424118734.6802443151901
654006540081.6439850127-91.296968349937840139.652983337316.6439850126699
663992239940.9552272182-285.08184265858340188.126615440418.9552272182118
674010740158.7108979733-181.3111455167440236.600247543551.710897973273
684016340148.1127950875-99.790905255996240277.6781101685-14.8872049125202
694011640028.1814151927-114.93738798631240318.7559727936-87.8185848072535
704011839997.9217098879-124.94914141877640363.0274315309-120.078290112113
714041640357.717532506166.983577225692740407.2988902682-58.2824674939038
724121541338.7684869413637.62688832316840453.6046247355123.768486941284
734085240865.7972734345338.29236736257540499.910359202913.7972734345385
744049740475.7397416307-27.862092065124640546.1223504344-21.2602583692933
754043040446.7933370071-179.12767867305840592.334341665916.7933370071114
764076640830.387580825461.454331566142640640.158087608564.3875808253506
774062640655.3151347989-91.296968349937840687.981833551129.3151347988751
784044240430.4652900446-285.08184265858340738.616552614-11.5347099554419
794059040572.0598738398-181.3111455167440789.251271677-17.940126160247
804067340606.4244845526-99.790905255996240839.3664207034-66.5755154473591
814066040545.4558182566-114.93738798631240889.4815697297-114.544181743426
824073640663.0456494135-124.94914141877640933.9034920053-72.954350586544
834108241118.691008493466.983577225692740978.325414280936.6910084933988
844187342088.0334415656637.62688832316841020.3396701112215.033441565611
854150741613.3537066959338.29236736257541062.3539259415106.353706695896
864110441127.02966815-27.862092065124641108.832423915123.0296681500258
874096340949.8167567844-179.12767867305841155.3109218887-13.1832432156007
884122741191.977395707161.454331566142641200.5682727267-35.0226042928698
894106340971.4713447851-91.296968349937841245.8256235648-91.528655214861
904087340744.2406216034-285.08184265858341286.8412210552-128.759378396622
914101640885.4543269711-181.3111455167441327.8568185456-130.545673028864
924143341591.877503829-99.790905255996241373.913401427158.877503829011
934134541384.9674036779-114.93738798631241419.969984308439.9674036779397
944137541401.1971198563-124.94914141877641473.752021562526.1971198562533
954159741599.482363957666.983577225692741527.53405881672.48236395762797
964222542230.7860241747637.62688832316841581.58708750215.78602417468937
974193741900.0675164498338.29236736257541635.6401161876-36.932483550183
984164241630.189306776-27.862092065124641681.6727852891-11.8106932240189
994155141553.4222242824-179.12767867305841727.70545439072.42222428238165
1004186641898.835164903861.454331566142641771.7105035332.835164903845
1014174441763.5814156806-91.296968349937841815.715552669319.5814156805936
1024161541648.6671917127-285.08184265858341866.414650945933.6671917126514
1034176441792.1973962942-181.3111455167441917.113749222528.1973962942211
1044182841783.3881555003-99.790905255996241972.4027497557-44.6118444997119
1054178641659.2456376974-114.93738798631242027.6917502889-126.754362302585
1064185241740.119145395-124.94914141877642088.8299960237-111.880854604962
1074218342149.048181015766.983577225692742149.9682417586-33.9518189842784
1084293743016.7545961585637.62688832316842219.618515518379.7545961585201
1094263542642.4388433594338.29236736257542289.2687892787.43884335938492
1104229242249.3463992802-27.862092065124642362.515692785-42.6536007198301
1114220242147.3650823812-179.12767867305842435.7625962919-54.6349176188087
1124257742586.35231771461.454331566142642506.19335071989.3523177140305
1134260042714.6728632022-91.296968349937842576.6241051478114.672863202162
1144243342508.7003367386-285.08184265858342642.3815059275.7003367385623
1154258442641.1722388245-181.3111455167442708.138906692357.1722388244743
1164266042649.7003122182-99.790905255996242770.0905930378-10.2996877817932
1174265942600.895108603-114.93738798631242832.0422793833-58.1048913970153
1184271242664.3393007691-124.94914141877642884.6098406496-47.6606992308516
1194303943073.839020858466.983577225692742937.177401915934.8390208583805
1204366443706.7721935764637.62688832316842983.600918100542.7721935763693
1214339743425.6831983524338.29236736257543030.02443428528.6831983524171
1224311043171.027874773-27.862092065124643076.834217292161.0278747730335
1234300543065.4836783739-179.12767867305843123.644000299260.4836783738865
1244315943085.804664631661.454331566142643170.7410038023-73.1953353684075
1254306643005.4589610446-91.296968349937843217.8380073054-60.5410389554163
1264297742973.699017308-285.08184265858343265.3828253506-3.30098269199516
1274313943146.3835021209-181.3111455167443312.92764339587.38350212093792
1284322643185.817537779-99.790905255996243365.973367477-40.1824622210406
1294324243179.918296428-114.93738798631243419.0190915583-62.0817035719665
1304334843341.7284955527-124.94914141877643479.2206458661-6.27150444730069
1314360543603.594222600466.983577225692743539.4222001739-1.40577739958098
1324422544206.1593766807637.62688832316843606.2137349961-18.8406233192945
1334398343954.7023628191338.29236736257543673.0052698184-28.2976371809491
1344375443793.2216802562-27.862092065124643742.640411808939.2216802562252
1354363243630.8521248736-179.12767867305843812.2755537994-1.14787512636394
1364386843792.714062118661.454331566142643881.8316063152-75.2859378813664
1374386443867.9093095189-91.296968349937843951.3876588313.90930951891642
1384380843882.9303513596-285.08184265858344018.15149129974.9303513596169
1394395444004.3958217498-181.3111455167444084.915323766950.3958217498293
1404403244012.1305820806-99.790905255996244151.6603231754-19.8694179194208
1414409044076.5320654024-114.93738798631244218.4053225839-13.4679345976183
1424421044267.1769648525-124.94914141877644277.772176566357.1769648525005
1434443544465.877392225766.983577225692744337.139030548630.8773922256805
1444491944821.527347028637.62688832316844378.8457646488-97.4726529719628
1454478544811.1551338885338.29236736257544420.55249874926.1551338884601
1464461644815.4617664248-27.862092065124644444.4003256403199.461766424785
1474449644702.8795261413-179.12767867305844468.2481525317206.879526141347
1484460044657.861826022161.454331566142644480.683842411857.8618260220828
1494446344524.1774360581-91.296968349937844493.119532291861.1774360581112
1504423244252.3879442788-285.08184265858344496.693898379820.3879442788239
1514424844177.042881049-181.3111455167444500.2682644677-70.9571189509516
1524428244162.0893364464-99.790905255996244501.7015688096-119.910663553572
1534431144233.8025148349-114.93738798631244503.1348731514-77.1974851651321
1544436244333.9530140321-124.94914141877644514.9961273867-28.0469859679215
1554461744640.159041152466.983577225692744526.85738162223.1590411523503
1564502244853.3229688538637.62688832316844553.050142823-168.677031146217
1574488244846.4647286133338.29236736257544579.2429040241-35.5352713867105
1584459444605.0632991653-27.862092065124644610.798792899811.0632991652747
1594450244540.7729968975-179.12767867305844642.354681775638.7729968974891
1604475244770.416634573761.454331566142644672.129033860118.4166345737249
1614469044769.3935824052-91.296968349937844701.903385944779.393582405246
1624453344624.0871678566-285.08184265858344726.99467480291.0871678566036
1634460444637.2251818575-181.3111455167444752.085963659333.2251818574732
1644464644615.7799540596-99.790905255996244776.0109511964-30.2200459403539
1654465244619.0014492529-114.93738798631244799.9359387334-32.9985507471283
1664471844735.7293806793-124.94914141877644825.219760739417.7293806793386
1674492844938.512840028966.983577225692744850.503582745410.5128400288668
1684528545053.6760004156637.62688832316844878.6971112613-231.32399958442
1694518345120.8169928604338.29236736257544906.8906397771-62.1830071396398
1704496445018.0676892569-27.862092065124644937.794402808254.067689256939
1714487544960.4295128337-179.12767867305844968.698165839385.4295128337471
1724507145078.110912038561.454331566142645002.43475639547.110912038479
1734498545025.1256213985-91.296968349937845036.171346951440.1256213984962
1744485444922.8704627503-285.08184265858345070.211379908368.8704627503103
1754492544927.0597326516-181.3111455167445104.25141286512.0597326516363
1764497044902.228243827-99.790905255996245137.562661429-67.7717561729514
1774501144966.0634779935-114.93738798631245170.8739099928-44.9365220064792
1784510745135.675560001-124.94914141877645203.273581417828.6755600009637
1794530645309.343169931566.983577225692745235.67325284283.34316993146786
1804577345640.9616440683637.62688832316845267.4114676085-132.038355931712
1814562545612.5579502632338.29236736257545299.1496823742-12.4420497368192
1824539145483.1295333833-27.862092065124645326.732558681892.1295333833477
1834532545474.8122436838-179.12767867305845354.3154349893149.812243683758
1844543045423.297984908861.454331566142645375.247683525-6.70201509118488
1854532145337.1170362892-91.296968349937845396.179932060816.1170362891571
1864523845354.622116101-285.08184265858345406.4597265575116.62211610104
1874524645256.5716244624-181.3111455167445416.739521054310.5716244624346
1884528145245.0556741905-99.790905255996245416.7352310655-35.944325809498
1894529745292.2064469096-114.93738798631245416.7309410767-4.79355309037783
1904534945412.2053285532-124.94914141877645410.743812865663.2053285532165
1914553645600.259738119966.983577225692745404.756684654464.259738119872
1924590345770.7397556695637.62688832316845397.6333560074-132.260244330522
1934571645703.1976052771338.29236736257545390.5100273603-12.8023947228576
1944541945482.7727278672-27.862092065124645383.089364197963.7727278671882
1954523745277.4589776375-179.12767867305845375.668701035640.4589776374705
1964534945271.751412296361.454331566142645364.7942561375-77.248587703667
1974526045257.3771571105-91.296968349937845353.9198112395-2.62284288951923
1984513945229.5900635746-285.08184265858345333.491779083990.5900635746439
1994515445176.2473985883-181.3111455167445313.063746928422.2473985883189
2004518645183.6630050347-99.790905255996245288.1279002213-2.33699496534246
2014526245375.745334472-114.93738798631245263.1920535143113.745334472049
2024522745337.2814488447-124.94914141877645241.6676925741110.281448844689
2034531345338.873091140466.983577225692745220.143331633925.8730911403909
2044556445286.8375543749637.62688832316845203.5355573019-277.162445625094
2054539245258.7798496675338.29236736257545186.9277829699-133.220150332512
2064511445078.8847790436-27.862092065124645176.9773130215-35.1152209563515
2074499645004.1008356-179.12767867305845167.0268430738.1008356000384
2084515945095.239904990161.454331566142645161.3057634438-63.7600950099222
2094510745149.7122845354-91.296968349937845155.584683814542.7122845354024
2104496345059.706203193-285.08184265858345151.375639465596.7062031930473
2114500545044.1445504002-181.3111455167445147.166595116539.1445504001967
2124502445003.5338759125-99.790905255996245144.2570293435-20.4661240875284
2134502545023.5899244158-114.93738798631245141.3474635705-1.41007558420097
2144505345092.0327250795-124.94914141877645138.916416339339.0327250794871
2154514345082.531053666266.983577225692745136.4853691081-60.4689463337636
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/19qbg1293643762.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/19qbg1293643762.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/29qbg1293643762.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/29qbg1293643762.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/310b11293643762.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/310b11293643762.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/410b11293643762.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/29/t1293643630muqpb8iwlr7mfeb/410b11293643762.ps (open in new window)


 
Parameters (Session):
par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;
 
Parameters (R input):
par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;
 
R code (references can be found in the software module):
par1 <- as.numeric(par1) #seasonal period
if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
par3 <- as.numeric(par3) #s.degree
if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
par5 <- as.numeric(par5)#t.degree
if (par6 != '') par6 <- as.numeric(par6)#l.window
par7 <- as.numeric(par7)#l.degree
if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
nx <- length(x)
x <- ts(x,frequency=par1)
if (par6 != '') {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
} else {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
}
m$time.series
m$win
m$deg
m$jump
m$inner
m$outer
bitmap(file='test1.png')
plot(m,main=main)
dev.off()
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Component',header=TRUE)
a<-table.element(a,'Window',header=TRUE)
a<-table.element(a,'Degree',header=TRUE)
a<-table.element(a,'Jump',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,m$win['s'])
a<-table.element(a,m$deg['s'])
a<-table.element(a,m$jump['s'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,m$win['t'])
a<-table.element(a,m$deg['t'])
a<-table.element(a,m$jump['t'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Low-pass',header=TRUE)
a<-table.element(a,m$win['l'])
a<-table.element(a,m$deg['l'])
a<-table.element(a,m$jump['l'])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Fitted',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Remainder',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]+m$time.series[i,'remainder'])
a<-table.element(a,m$time.series[i,'seasonal'])
a<-table.element(a,m$time.series[i,'trend'])
a<-table.element(a,m$time.series[i,'remainder'])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
 




Copyright

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.


Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

  • personalize online software applications according to your needs
  • enforce strict security rules with respect to the data that you upload (e.g. statistical data)
  • manage user sessions of online applications
  • alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

FreeStatistics.org is powered by