what's wrong with diff.zoo

Its best to cut down your data as much as possible when posting.
Using the first 10 rows of PPP seems sufficient to illustrate this:

  

P <- head(PPP, 10)
diff(P)
    

           PriceIT    PriceUS    ExRateUSIT
1973(4)  0.2000008 0.29999924 -6.330707e-05
1973(7)  0.1000004 0.09999847  4.078149e-05
1973(10) 0.2000008 0.39999771 -3.498323e-06

Here is the dput output for just those 10 rows in case there are follow ups:

P <- structure(c(19.60000038147, 19.70000076294, 20, 20.20000076294,
20.5, 20.60000038147, 20.70000076294, 20.70000076294, 21, 21.20000076294,
42.5999984741, 42.9000015259, 43.2999992371, 43.5999984741, 43.9000015259,
44.2000007629, 44.2999992371, 45.0999984741, 45.2000007629, 45.5999984741,
0.00170791273132914, 0.00174209951913706, 0.00176040845258218,
0.00169710137902025, 0.00169609381850337, 0.0016792046735684,
0.00171998616788486, 0.00174231201103162, 0.0017690973759385,
0.00176559905254172), .Dim = c(10L, 3L), .Dimnames = list(NULL,
    c("PriceIT", "PriceUS", "ExRateUSIT")), index = c(1973, 1973.08333333333,
1973.16666666667, 1973.25, 1973.33333333333, 1973.41666666667,
1973.5, 1973.58333333333, 1973.66666666667, 1973.75), class = c("zooreg",
"zoo"), frequency = 12)

The problem appears to be small differences between P and lag(P, -1).
Note sure if this is a problem with this specific object (how was it
created?) or if its a general problem.  We can see the problem by
merging P with lag(P, -1) :

  

merge(P, lag(P, -1))
    

                   PriceIT.P PriceUS.P ExRateUSIT.P PriceIT.lag(P, -1)
PriceUS.lag(P, -1) ExRateUSIT.lag(P, -1)
1973(1)                 19.6      42.6  0.001707913                 NA
                NA                    NA
1973(26178848280)       19.7      42.9  0.001742100                 NA
                NA                    NA
1973(26178848281)         NA        NA           NA               19.6
              42.6           0.001707913
1973(52357696562)         NA        NA           NA               19.7
              42.9           0.001742100
1973(52357696563)       20.0      43.3  0.001760408                 NA
                NA                    NA
1973(78536544842)       20.2      43.6  0.001697101               20.0
              43.3           0.001760408
1973(104715393122)      20.5      43.9  0.001696094                 NA
                NA                    NA
1973(104715393123)        NA        NA           NA               20.2
              43.6           0.001697101
1973(130894241403)        NA        NA           NA               20.5
              43.9           0.001696094
1973(130894241404)      20.6      44.2  0.001679205                 NA
                NA                    NA
1973(157073089683)      20.7      44.3  0.001719986               20.6
              44.2           0.001679205
1973(183251937963)      20.7      45.1  0.001742312                 NA
                NA                    NA
1973(183251937964)        NA        NA           NA               20.7
              44.3           0.001719986
1973(209430786244)        NA        NA           NA               20.7
              45.1           0.001742312
1973(209430786245)      21.0      45.2  0.001769097                 NA
                NA                    NA
1973(235609634525)      21.2      45.6  0.001765599               21.0
              45.2           0.001769097
1973(261788482805)        NA        NA           NA               21.2
              45.6           0.001765599

Will look at the problem but in the meantime here are three workarounds:

  

# 1. fix up the time scale as it seems slightly off a 12 point cycle
P0 <- aggregate(P, round(12 * time(P))/12, identity)
diff(P0)
    

           PriceIT    PriceUS    ExRateUSIT
1973(2)  0.1000004 0.30000305  3.418679e-05
1973(3)  0.2999992 0.39999771  1.830893e-05
1973(4)  0.2000008 0.29999924 -6.330707e-05
1973(5)  0.2999992 0.30000305 -1.007561e-06
1973(6)  0.1000004 0.29999924 -1.688914e-05
1973(7)  0.1000004 0.09999847  4.078149e-05
1973(8)  0.0000000 0.79999924  2.232584e-05
1973(9)  0.2999992 0.10000229  2.678536e-05
1973(10) 0.2000008 0.39999771 -3.498323e-06

  

# 2. use zoo instead of zooreg
diff(as.zoo(P))
    

            PriceIT    PriceUS    ExRateUSIT
1973.0833 0.1000004 0.30000305  3.418679e-05
1973.1667 0.2999992 0.39999771  1.830893e-05
1973.25   0.2000008 0.29999924 -6.330707e-05
1973.3333 0.2999992 0.30000305 -1.007561e-06
1973.4167 0.1000004 0.29999924 -1.688914e-05
1973.5    0.1000004 0.09999847  4.078149e-05
1973.5833 0.0000000 0.79999924  2.232584e-05
1973.6667 0.2999992 0.10000229  2.678536e-05
1973.75   0.2000008 0.39999771 -3.498323e-06

  

# 3. assuming this is monthly data use yearmon class
Pym <- aggregate(P, as.yearmon, identity)
diff(Pym)
    

           PriceIT    PriceUS    ExRateUSIT
Feb 1973 0.1000004 0.30000305  3.418679e-05
Mar 1973 0.2999992 0.39999771  1.830893e-05
Apr 1973 0.2000008 0.29999924 -6.330707e-05
May 1973 0.2999992 0.30000305 -1.007561e-06
Jun 1973 0.1000004 0.29999924 -1.688914e-05
Jul 1973 0.1000004 0.09999847  4.078149e-05
Aug 1973 0.0000000 0.79999924  2.232584e-05
Sep 1973 0.2999992 0.10000229  2.678536e-05
Oct 1973 0.2000008 0.39999771 -3.498323e-06


On Sun, Mar 7, 2010 at 7:46 AM, mat <matthieu.stigler at gmail.com> wrote:
  

Hi all

I have a strange output using diff.zoo, where diff reduces the dim object by
more than 1:

See:
    

class(PPP)
      

[1] "zooreg" "zoo"  > frequency(PPP)
[1] 12
    

dim(PPP)
      

[1] 202   3
    

dim(diff(PPP))
      

[1] 67  3

#What is happening? Dim is not 201 3 as I would expect, like I get with ts:
    

dim(diff(as.ts(PPP)))
      

[1] 201   3

#Differentiation seems to be done only for selected months...
    

head(PPP)
      

        PriceIT   PriceUS ExRateUSIT
1973(1) 0.0000000 0.0000000  0.0000000
1973(2) 0.5089089 0.7017644  1.9819006
1973(3) 2.0202688 1.6298400  3.0273857
1973(4) 3.0153056 2.3202898 -0.6350275
1973(5) 4.4895300 3.0060137 -0.6944147
1973(6) 4.9761509 3.6870589 -1.6951727
    

head(diff(PPP))
      

         PriceIT   PriceUS ExRateUSIT
1973(4)  0.9950369 0.6904498 -3.6624133
1973(7)  0.4842643 0.2259853  2.3995976
1973(10) 0.9478780 0.8810579 -0.1979420
1974(1)  1.3730158 0.8620694 -6.4295795
1974(4)  1.2959112 0.4175387  0.2104218
1974(7)  2.4591418 0.8130157  0.9254661

#Series is from:
library(zoo)
source("priceLev.R") #see below

Thanks a lot for your help, I'm really stuck...

Mat

I had problems copy/paste this directly into R console, but saving it as
priceLev.R and sourcing it was ok:


PPP<-structure(c(19.60000038147, 19.70000076294, 20, 20.20000076294,
20.5, 20.60000038147, 20.70000076294, 20.70000076294, 21, 21.20000076294,
21.29999923706, 21.70000076294, 22, 22.39999961853, 23, 23.29999923706,
23.70000076294, 24.10000038147, 24.70000076294, 25.20000076294,
26, 26.5, 27, 27.10000038147, 27.5, 27.89999961853, 27.89999961853,
28.20000076294, 28.5, 28.79999923706, 28.89999961853, 29.10000038147,
29.29999923706, 29.70000076294, 30, 30.29999923706, 30.5, 31,
31.70000076294, 32.70000076294, 33.20000076294, 33.29999923706,
33.5, 33.79999923706, 34.40000152588, 35.59999847412, 36.29999923706,
36.79999923706, 37.29999923706, 38.09999847412, 38.79999923706,
39.20000076294, 39.70000076294, 40, 40.29999923706, 40.70000076294,
41.09999847412, 41.40000152588, 42.09999847412, 42.29999923706,
42.79999923706, 43.20000076294, 43.59999847412, 44.09999847412,
44.59999847412, 44.90000152588, 45.29999923706, 45.40000152588,
46.09999847412, 46.59999847412, 47, 47.40000152588, 48.29999923706,
48.90000152588, 49.70000076294, 50.40000152588, 51.09999847412,
51.59999847412, 52, 52.59999847412, 53.79999923706, 55.09999847412,
55.70000076294, 56.70000076294, 58.5, 59.59999847412, 60.20000076294,
61, 61.59999847412, 62.09999847412, 63.20000076294, 63.90000152588,
65.30000305176, 66.40000152588, 67.80000305176, 68.69999694824,
69.90000152588, 71.19999694824, 72.19999694824, 73.30000305176,
74.19999694824, 75, 75.69999694824, 76.19999694824, 77.30000305176,
78.69999694824, 80.09999847412, 80.90000152588, 82, 83.09999847412,
83.80000305176, 84.5, 85.5, 86.40000152588, 87.69999694824, 89.30000305176,
90.5, 92.30000305176, 93.5, 94.09999847412, 95.40000152588, 96.80000305176,
97.59999847412, 98.59999847412, 99.59999847412, 100.19999694824,
101.09999847412, 101.5, 102.80000305176, 104.5, 105.59999847412,
106.09999847412, 107.40000152588, 108.5, 109.19999694824, 110.09999847412,
110.69999694824, 111.30000305176, 111.69999694824, 112, 112.90000152588,
114, 114.69999694824, 115.40000152588, 116.59999847412, 117.80000305176,
118.69999694824, 119.69999694824, 120.40000152588, 121, 121.5,
121.69999694824, 122.19999694824, 123.69999694824, 124.5, 125.30000305176,
126, 126.80000305176, 127.30000305176, 127.59999847412, 128.10000610352,
128.60000610352, 128.60000610352, 128.89999389648, 129.19999694824,
130, 130.39999389648, 130.80000305176, 131.60000610352, 132.10000610352,
132.60000610352, 133, 133.5, 133.89999389648, 134.30000305176,
134.69999694824, 135.60000610352, 136.89999389648, 137.19999694824,
137.5, 138.19999694824, 138.5, 139.19999694824, 139.60000610352,
140, 140.5, 140.89999389648, 141.5, 142.19999694824, 143.30000305176,
144.5, 145, 146.10000610352, 147.30000305176, 148, 149, 149.60000610352,
150.30000305176, 150.69999694824, 150.89999389648, 151.60000610352,
153.10000610352, 42.5999984741, 42.9000015259, 43.2999992371,
43.5999984741, 43.9000015259, 44.2000007629, 44.2999992371, 45.0999984741,
45.2000007629, 45.5999984741, 45.9000015259, 46.2000007629, 46.5999984741,
47.2000007629, 47.7999992371, 48, 48.5999984741, 49, 49.4000015259,
50, 50.5999984741, 51.0999984741, 51.5, 51.9000015259, 52.0999984741,
52.5, 52.7000007629, 52.9000015259, 53.2000007629, 53.5999984741,
54.2000007629, 54.2999992371, 54.5999984741, 54.9000015259, 55.2999992371,
55.5, 55.5999984741, 55.7999992371, 55.9000015259, 56.0999984741,
56.5, 56.7999992371, 57.0999984741, 57.4000015259, 57.5999984741,
57.9000015259, 58, 58.2000007629, 58.5, 59.0999984741, 59.5,
60, 60.2999992371, 60.7000007629, 61, 61.2000007629, 61.4000015259,
61.5999984741, 61.9000015259, 62.0999984741, 62.5, 62.9000015259,
63.4000015259, 63.9000015259, 64.5, 65.1999969482, 65.6999969482,
66, 66.5, 67.0999984741, 67.4000015259, 67.6999969482, 68.3000030518,
69.0999984741, 69.8000030518, 70.5999984741, 71.5, 72.3000030518,
73.0999984741, 73.8000030518, 74.5999984741, 75.1999969482, 75.9000015259,
76.6999969482, 77.8000030518, 78.9000015259, 80.0999984741, 81,
81.8000030518, 82.6999969482, 82.6999969482, 83.3000030518, 84,
84.8000030518, 85.5, 86.3000030518, 87, 87.9000015259, 88.5,
89.0999984741, 89.8000030518, 90.5999984741, 91.5999984741, 92.3000030518,
93.1999969482, 93.4000015259, 93.6999969482, 94, 94.3000030518,
94.5999984741, 94.5, 94.9000015259, 95.8000030518, 97, 97.5,
97.6999969482, 97.9000015259, 98.1999969482, 98, 97.5999984741,
97.8000030518, 97.9000015259, 97.9000015259, 98.5999984741, 99.1999969482,
99.5, 99.9000015259, 100.1999969482, 100.6999969482, 101, 101.1999969482,
101.3000030518, 101.9000015259, 102.4000015259, 102.5999984741,
103.0999984741, 103.4000015259, 103.6999969482, 104.0999984741,
104.5, 105, 105.3000030518, 105.3000030518, 105.3000030518, 105.5,
106, 106.4000015259, 106.9000015259, 107.3000030518, 107.5999984741,
107.8000030518, 108, 108.3000030518, 108.6999969482, 109, 109.3000030518,
109.5999984741, 109.3000030518, 108.8000030518, 108.5999984741,
108.9000015259, 109.5, 109.5, 109.6999969482, 110.1999969482,
110.3000030518, 110.4000015259, 110.5, 111.1999969482, 111.5999984741,
112.0999984741, 112.6999969482, 113.0999984741, 113.5, 113.8000030518,
114.4000015259, 115, 115.3000030518, 115.4000015259, 115.4000015259,
115.6999969482, 116, 116.5, 117.0999984741, 117.5, 118, 118.5,
119, 119.8000030518, 120.1999969482, 120.3000030518, 120.5, 121.0999984741,
121.5999984741, 122.3000030518, 123.0999984741, 123.8000030518,
124.0999984741, 124.4000015259, 124.5999984741, 125, 125.5999984741,
0.00170791273132914, 0.00174209951913706, 0.00176040845258218,
0.00169710137902025, 0.00169609381850337, 0.0016792046735684,
0.00171998616788486, 0.00174231201103162, 0.00176909737593850,
0.00176559905254172, 0.00169038840243291, 0.00164579257106955,
0.00154330508995765, 0.00152751052610713, 0.00156870134431149,
0.00157200571003395, 0.00158080266451816, 0.00153789372388514,
0.00155219247186651, 0.00152690408919378, 0.00151030025882740,
0.0014992053772286, 0.00149961004098130, 0.00151791138210253,
0.00155041165776418, 0.00156779122961396, 0.00158420865760686,
0.00157669023618497, 0.00159370176532851, 0.00159820997361459,
0.00153869820346857, 0.00149628918637955, 0.00147399143728242,
0.00147449127396179, 0.00147210366254964, 0.001464493321869,
0.00142450142450142, 0.00130210030432208, 0.00121129900062598,
0.00113710017662363, 0.00116759682220348, 0.00117799501854215,
0.00119430080008036, 0.00119360230910755, 0.00118369811305430,
0.00116840174992149, 0.00115540150202195, 0.00115210030473245,
0.00113720364788047, 0.00113269527966656, 0.00112759908181671,
0.00112640515330342, 0.00112790438476952, 0.00112949684031799,
0.00113300327052292, 0.00113319581068863, 0.0011317978765388,
0.00113530572839516, 0.00113879652617039, 0.00114160461084470,
0.00114689423295764, 0.00116189904399275, 0.00116919410456185,
0.00116440190827110, 0.00114880470740695, 0.00116339946972441,
0.00118040065178541, 0.00119520008695516, 0.00120499348594498,
0.00123169392646559, 0.00118570513198108, 0.00118629587872915,
0.00119550017935439, 0.00118989544621630, 0.00118880621116386,
0.00118580356321465, 0.00117439812096301, 0.00118280204099774,
0.00121919992832387, 0.00122189634673585, 0.00123260489724270,
0.00121119629142077, 0.00121119629142077, 0.00123289363839214,
0.00124269912368631, 0.00123459841491511, 0.00116349423223834,
0.00114169585595958, 0.00118600047471892, 0.00119730364063127,
0.00120260238929126, 0.00118009415111576, 0.00117420504297619,
0.00114409932379843, 0.00110000106750649, 0.00107040024502102,
0.00104718620797518, 0.000980613256761468, 0.000969649910456641,
0.000927867583147656, 0.000876370465502322, 0.000843525938422606,
0.000823295979829121, 0.000803735801681492, 0.000842027275228413,
0.000837303506576214, 0.00083921485467683, 0.000828939961655155,
0.000814186402967888, 0.000791652779081, 0.000773221759850004,
0.000756658609619449, 0.00077919851937074, 0.000736143901754949,
0.000723452890870574, 0.000718081299390519, 0.00070862183088102,
0.000694473409094806, 0.000680809361993181, 0.000714929155512817,
0.00072742616872993, 0.000714397961872782, 0.000699437666460164,
0.00068853453006531, 0.000681310291427974, 0.00066182213723944,
0.000652141291441826, 0.000629033682327389, 0.000623978237540331,
0.000631787746464218, 0.000615085574381394, 0.000599923208071712,
0.000585950087094921, 0.000600099611261314, 0.000619513417282865,
0.000610321768907887, 0.000589511431606801, 0.000590040105729007,
0.000571043507422813, 0.000561649461352701, 0.000534533528145891,
0.000526598495131594, 0.000536754233000383, 0.000522870343728599,
0.000513146818997007, 0.000489715964740451, 0.000481116189559779,
0.000506101044383357, 0.000503917974554817, 0.000511791668803899,
0.000526224404774398, 0.000533757489838498, 0.000525370111122406,
0.000560089149346125, 0.000570216463691828, 0.000583600817041144,
0.000601272286874565, 0.000629639672710148, 0.000645815416462228,
0.000641251743442265, 0.000654236179260713, 0.000652273182391623,
0.000676448079471965, 0.000704061753916339, 0.000709104198499191,
0.000720632404196826, 0.000713735141009144, 0.000724931887198181,
0.000759203418417369, 0.0007705703819913, 0.000765755403403666,
0.000773419154661628, 0.000774713326752632, 0.000759589821496392,
0.000747406521267597, 0.000743947953430204, 0.000762857979627377,
0.00076770719167874, 0.000807174154425746, 0.000830744187376882,
0.000821773713091906, 0.000800243277082303, 0.000806016075652368,
0.00080580827232252, 0.000794401024342725, 0.000765954804926349,
0.00073138978164888, 0.000715343373114671, 0.00071779778378185,
0.000738901704515748, 0.000769100631071927, 0.000771837212823204,
0.000743428098333353, 0.000737854892260688, 0.000728597449908925,
0.000728969211551167, 0.000706299507030033, 0.000697155593265228,
0.000731320244617571, 0.000722418082886736, 0.00071215938252162,
0.000730332160273162), .Dim = c(202L, 3L), .Dimnames = list(NULL,
  c("PriceIT", "PriceUS", "ExRateUSIT")), index = c(1973,
1973.08333333333, 1973.16666666667, 1973.25, 1973.33333333333,
1973.41666666667, 1973.5, 1973.58333333333, 1973.66666666667,
1973.75, 1973.83333333333, 1973.91666666667, 1974, 1974.08333333333,
1974.16666666667, 1974.25, 1974.33333333333, 1974.41666666667,
1974.5, 1974.58333333333, 1974.66666666667, 1974.75, 1974.83333333333,
1974.91666666667, 1975, 1975.08333333333, 1975.16666666667, 1975.25,
1975.33333333333, 1975.41666666667, 1975.5, 1975.58333333333,
1975.66666666667, 1975.75, 1975.83333333333, 1975.91666666667,
1976, 1976.08333333333, 1976.16666666667, 1976.25, 1976.33333333333,
1976.41666666667, 1976.5, 1976.58333333333, 1976.66666666667,
1976.75, 1976.83333333333, 1976.91666666667, 1977, 1977.08333333333,
1977.16666666667, 1977.25, 1977.33333333333, 1977.41666666667,
1977.5, 1977.58333333333, 1977.66666666667, 1977.75, 1977.83333333333,
1977.91666666667, 1978, 1978.08333333333, 1978.16666666667, 1978.25,
1978.33333333333, 1978.41666666667, 1978.5, 1978.58333333333,
1978.66666666667, 1978.75, 1978.83333333333, 1978.91666666667,
1979, 1979.08333333333, 1979.16666666667, 1979.25, 1979.33333333333,
1979.41666666667, 1979.5, 1979.58333333333, 1979.66666666667,
1979.75, 1979.83333333333, 1979.91666666667, 1980, 1980.08333333333,
1980.16666666667, 1980.25, 1980.33333333333, 1980.41666666667,
1980.5, 1980.58333333333, 1980.66666666667, 1980.75, 1980.83333333333,
1980.91666666667, 1981, 1981.08333333333, 1981.16666666667, 1981.25,
1981.33333333333, 1981.41666666667, 1981.5, 1981.58333333333,
1981.66666666667, 1981.75, 1981.83333333333, 1981.91666666667,
1982, 1982.08333333333, 1982.16666666667, 1982.25, 1982.33333333333,
1982.41666666667, 1982.5, 1982.58333333333, 1982.66666666667,
1982.75, 1982.83333333333, 1982.91666666667, 1983, 1983.08333333333,
1983.16666666667, 1983.25, 1983.33333333333, 1983.41666666667,
1983.5, 1983.58333333333, 1983.66666666667, 1983.75, 1983.83333333333,
1983.91666666667, 1984, 1984.08333333333, 1984.16666666667, 1984.25,
1984.33333333333, 1984.41666666667, 1984.5, 1984.58333333333,
1984.66666666667, 1984.75, 1984.83333333333, 1984.91666666667,
1985, 1985.08333333333, 1985.16666666667, 1985.25, 1985.33333333333,
1985.41666666667, 1985.5, 1985.58333333333, 1985.66666666667,
1985.75, 1985.83333333333, 1985.91666666667, 1986, 1986.08333333333,
1986.16666666667, 1986.25, 1986.33333333333, 1986.41666666667,
1986.5, 1986.58333333333, 1986.66666666667, 1986.75, 1986.83333333333,
1986.91666666667, 1987, 1987.08333333333, 1987.16666666667, 1987.25,
1987.33333333333, 1987.41666666667, 1987.5, 1987.58333333333,
1987.66666666667, 1987.75, 1987.83333333333, 1987.91666666667,
1988, 1988.08333333333, 1988.16666666667, 1988.25, 1988.33333333333,
1988.41666666667, 1988.5, 1988.58333333333, 1988.66666666667,
1988.75, 1988.83333333333, 1988.91666666667, 1989, 1989.08333333333,
1989.16666666667, 1989.25, 1989.33333333333, 1989.41666666667,
1989.5, 1989.58333333333, 1989.66666666667, 1989.75), class = c("zooreg",
"zoo"), frequency = 12)


sessionInfo()
R version 2.9.2 (2009-08-24)
x86_64-pc-linux-gnu

locale:
LC_CTYPE=fr_CH.UTF-8;LC_NUMERIC=C;LC_TIME=fr_CH.UTF-8;LC_COLLATE=fr_CH.UTF-8;LC_MONETARY=fr_CH.UTF-8;LC_MESSAGES=fr_CH.UTF-8;LC_PAPER=fr_CH.UTF-8;LC_NAME=fr_CH.UTF-8;LC_ADDRESS=fr_CH.UTF-8;LC_TELEPHONE=fr_CH.UTF-8;LC_MEASUREMENT=fr_CH.UTF-8;LC_IDENTIFICATION=fr_CH.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base
other attached packages:
[1] zoo_1.6-2    rkward_0.5.1

loaded via a namespace (and not attached):
[1] grid_2.9.2      lattice_0.17-26 tools_2.9.2