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cut variable within a loop

5 messages · Janka Vanschoenwinkel, David Winsemius, Janka VANSCHOENWINKEL

#
Hi Petr,

Here the code below:

load("data.Rda") # or see data at the bottom of this email

##########################################################################################

####### Question cut2 intervals #######

# I have the variable irrigation which has a range from 0% to 100%.
# I now want to calculate the code below for different thresholds of irrigation.
# So for instance: starting from 10%, a farmer is defined as "irrigated farm".
# Then we would have 0-10 = Rainfed, 10-100 is Irrigated.

# In the code below I run a short code for only 50 observations and
# only for the interval 0-1,1-100 and 0-2, 2-100. If that works, it should also
# work for 1-99.

# As indicated, it goes wrong when I want to cut based on the "i"
specified at the start of the loop.

# Thanks a lot for your help!

# Janka


d= data.frame(MEt_Rainfed=rep(1,2),MEp_Rainfed=rep(1,2),MEt_Irrigation=rep(1,2),MEp_Irrigation=rep(1,2))

library(Hmisc)
o<-lapply(1:2, function(i){

  #cut sample in rainfed versus irrigation
  Alldata$irri=cut2(Alldata$irrigation,i)
  levels(Alldata$irri)<-c("0","1")

  Alldata_Rainfed<-subset(Alldata, irri == 0)
  Alldata_Irrigation<-subset(Alldata, irri == 1)

  Alldata_Rainfed$w<-Alldata_Rainfed$b48+Alldata_Rainfed$b50
  Alldata_Irrigation$w<-Alldata_Irrigation$b48+Alldata_Irrigation$b50

  OLS_Rainfed <- lm(LnALVperHA~ps1+ps2+ps3+ps4+ts1+ts2+ts3+ts4+
                      ps1sq+ps2sq+ps3sq+ps4sq+ts1sq+ts2sq+ts3sq+ts4sq+
                      pdnsty+portsML+cities500k+rentedland+subsidies1+
                      elevmean+elevrange+
                      t_gravel+t_gravel+t_ph_h2o+t_silt+t_sand+
                      AT+BE+DK+ES+FI+FR+GR+IE+IT+LU+NL+PT+SE+WDE+EDE+UK,
                    weights=w,Alldata_Rainfed)

  attach(Alldata_Rainfed)

  CoefRainfed_ps1 <- OLS_Rainfed$coeff[2]
  CoefRainfed_ps2 <- OLS_Rainfed$coeff[3]
  CoefRainfed_ps3 <- OLS_Rainfed$coeff[4]
  CoefRainfed_ps4 <- OLS_Rainfed$coeff[5]
  CoefRainfed_ts1 <- OLS_Rainfed$coeff[6]
  CoefRainfed_ts2 <- OLS_Rainfed$coeff[7]
  CoefRainfed_ts3 <- OLS_Rainfed$coeff[8]
  CoefRainfed_ts4 <- OLS_Rainfed$coeff[9]
  CoefRainfed_ps1sq <- OLS_Rainfed$coeff[10]
  CoefRainfed_ps2sq <- OLS_Rainfed$coeff[11]
  CoefRainfed_ps3sq <- OLS_Rainfed$coeff[12]
  CoefRainfed_ps4sq <- OLS_Rainfed$coeff[13]
  CoefRainfed_ts1sq <- OLS_Rainfed$coeff[14]
  CoefRainfed_ts2sq <- OLS_Rainfed$coeff[15]
  CoefRainfed_ts3sq <- OLS_Rainfed$coeff[16]
  CoefRainfed_ts4sq <- OLS_Rainfed$coeff[17]

  attach(Alldata_Rainfed)


  ###### MARGINAL EFFECTS SEASONAL and YEARLY and REGIONAL (EU or COUNTRY level)
  # Maar dit is dus de marginale impact per LnALVperHA?

  Alldata_Rainfed$MEts1 =
CoefRainfed_ts1+2*CoefRainfed_ts1sq*Alldata_Rainfed$ts1
  Alldata_Rainfed$MEts2 =
CoefRainfed_ts2+2*CoefRainfed_ts2sq*Alldata_Rainfed$ts2
  Alldata_Rainfed$MEts3 =
CoefRainfed_ts3+2*CoefRainfed_ts3sq*Alldata_Rainfed$ts3
  Alldata_Rainfed$MEts4 =
CoefRainfed_ts4+2*CoefRainfed_ts4sq*Alldata_Rainfed$ts4
  Alldata_Rainfed$MEt   = Alldata_Rainfed$MEts1 +
Alldata_Rainfed$MEts2 + Alldata_Rainfed$MEts3 + Alldata_Rainfed$MEts4

  Alldata_Rainfed$MEps1 =
CoefRainfed_ps1+2*CoefRainfed_ps1sq*Alldata_Rainfed$ps1
  Alldata_Rainfed$MEps2 =
CoefRainfed_ps2+2*CoefRainfed_ps2sq*Alldata_Rainfed$ps2
  Alldata_Rainfed$MEps3 =
CoefRainfed_ps3+2*CoefRainfed_ps3sq*Alldata_Rainfed$ps3
  Alldata_Rainfed$MEps4 =
CoefRainfed_ps4+2*CoefRainfed_ps4sq*Alldata_Rainfed$ps4
  Alldata_Rainfed$MEp   = Alldata_Rainfed$MEps1 +
Alldata_Rainfed$MEps2 + Alldata_Rainfed$MEps3 + Alldata_Rainfed$MEps4


  Alldata_Rainfed$weight2<-Alldata_Rainfed$b48+Alldata_Rainfed$b50
  attach(Alldata_Rainfed)
  library(stats)
  MEt_Rainfed<-weighted.mean(MEt,weight2)
  MEp_Rainfed<-weighted.mean(MEp,weight2)



  attach(Alldata_Irrigation)

  OLS_Irrigation <- lm(LnALVperHA~ps1+ps2+ps3+ps4+ts1+ts2+ts3+ts4+
                         ps1sq+ps2sq+ps3sq+ps4sq+ts1sq+ts2sq+ts3sq+ts4sq+
                         pdnsty+portsML+cities500k+rentedland+subsidies1+
                         elevmean+elevrange+
                         t_gravel+t_gravel+t_ph_h2o+t_silt+t_sand+
                         AT+BE+DK+ES+FI+FR+GR+IE+IT+LU+NL+PT+SE+WDE+EDE+UK,
                       weights=w,Alldata_Irrigation)



  CoefIrrigation_ps1 <- OLS_Irrigation$coeff[2]
  CoefIrrigation_ps2 <- OLS_Irrigation$coeff[3]
  CoefIrrigation_ps3 <- OLS_Irrigation$coeff[4]
  CoefIrrigation_ps4 <- OLS_Irrigation$coeff[5]
  CoefIrrigation_ts1 <- OLS_Irrigation$coeff[6]
  CoefIrrigation_ts2 <- OLS_Irrigation$coeff[7]
  CoefIrrigation_ts3 <- OLS_Irrigation$coeff[8]
  CoefIrrigation_ts4 <- OLS_Irrigation$coeff[9]
  CoefIrrigation_ps1sq <- OLS_Irrigation$coeff[10]
  CoefIrrigation_ps2sq <- OLS_Irrigation$coeff[11]
  CoefIrrigation_ps3sq <- OLS_Irrigation$coeff[12]
  CoefIrrigation_ps4sq <- OLS_Irrigation$coeff[13]
  CoefIrrigation_ts1sq <- OLS_Irrigation$coeff[14]
  CoefIrrigation_ts2sq <- OLS_Irrigation$coeff[15]
  CoefIrrigation_ts3sq <- OLS_Irrigation$coeff[16]
  CoefIrrigation_ts4sq <- OLS_Irrigation$coeff[17]

  attach(Alldata_Irrigation)
  # gives the residual errors in Y
  Alldata_Irrigation$residuals <-resid(OLS_Irrigation)

  # gives the predicted values for Ln_Y
  Alldata_Irrigation$Ln_y_hat <-fitted(OLS_Irrigation)

  # Zelf functie rmse maken
  rmse <- function(error)
  {
    sqrt(mean(error^2))
  }
  Alldata_Irrigation$y_hat <-
exp(Alldata_Irrigation$Ln_y_hat)*exp(0.5*(rmse(OLS_Irrigation$residuals))^2)

  # absolute impact (landwaarde current)
  Alldata_Irrigation$absolute.current<-Alldata_Irrigation$y_hat*Alldata_Irrigation$se025*Alldata_Irrigation$sys02


  ###### MARGINAL EFFECTS SEASONAL and YEARLY and REGIONAL (EU or COUNTRY level)
  # Maar dit is dus de marginale impact per LnALVperHA?

  Alldata_Irrigation$MEts1 =
CoefIrrigation_ts1+2*CoefIrrigation_ts1sq*Alldata_Irrigation$ts1
  Alldata_Irrigation$MEts2 =
CoefIrrigation_ts2+2*CoefIrrigation_ts2sq*Alldata_Irrigation$ts2
  Alldata_Irrigation$MEts3 =
CoefIrrigation_ts3+2*CoefIrrigation_ts3sq*Alldata_Irrigation$ts3
  Alldata_Irrigation$MEts4 =
CoefIrrigation_ts4+2*CoefIrrigation_ts4sq*Alldata_Irrigation$ts4
  Alldata_Irrigation$MEt   = Alldata_Irrigation$MEts1 +
Alldata_Irrigation$MEts2 + Alldata_Irrigation$MEts3 +
Alldata_Irrigation$MEts4

  Alldata_Irrigation$MEps1 =
CoefIrrigation_ps1+2*CoefIrrigation_ps1sq*Alldata_Irrigation$ps1
  Alldata_Irrigation$MEps2 =
CoefIrrigation_ps2+2*CoefIrrigation_ps2sq*Alldata_Irrigation$ps2
  Alldata_Irrigation$MEps3 =
CoefIrrigation_ps3+2*CoefIrrigation_ps3sq*Alldata_Irrigation$ps3
  Alldata_Irrigation$MEps4 =
CoefIrrigation_ps4+2*CoefIrrigation_ps4sq*Alldata_Irrigation$ps4
  Alldata_Irrigation$MEp   = Alldata_Irrigation$MEps1 +
Alldata_Irrigation$MEps2 + Alldata_Irrigation$MEps3 +
Alldata_Irrigation$MEps4


  Alldata_Irrigation$weight2<-Alldata_Irrigation$sys02*Alldata_Irrigation$se025
  Alldata_Irrigation$weight2<-Alldata_Irrigation$b48+Alldata_Irrigation$b50

  attach(Alldata_Irrigation)
  library(stats)
  MEt_Irrigation<-weighted.mean(MEt,weight2)
  MEp_Irrigation<-weighted.mean(MEp,weight2)

  c(MEt_Rainfed,MEp_Rainfed,MEt_Irrigation,MEp_Irrigation)

  attach(Alldata)


  # And in the loop (index i):

  d[i, ] = c(MEt_Rainfed,MEp_Rainfed,MEt_Irrigation,MEp_Irrigation)


})
out<-as.data.frame(do.call(rbind, o))




And the data are:

structure(list(LnALVperHA = c(8.09964942932129, 9.53274631500244,
7.42697763442993, 8.25370121002197, 8.42619132995605, 8.0093936920166,
8.09785747528076, 8.49044704437256, 9.08215141296387, 8.38935947418213,
8.67814350128174, 8.38935947418213, 10.4056901931763, 8.48210144042969,
8.30281829833984, 8.92265796661377, 8.33178997039795, 4.54404163360596,
10.662184715271, 9.62167072296143, 7.98790407180786, 7.58244323730469,
7.23262739181519, 9.47037124633789, 8.93403625488281, 7.54256629943848,
9.40302467346191, 10.6290521621704, 8.59830188751221, 8.59585666656494,
9.10000514984131, 9.99381542205811, 9.54681301116943, 9.53055191040039,
8.67971229553223, 7.19780731201172, 8.90067958831787, 6.0509786605835,
6.55788946151733, 8.22567272186279, 9.05618953704834, 6.81858921051025,
8.46410751342773, 7.81292057037354, 8.38989448547363, 10.4709157943726,
8.06132888793945, 8.43629264831543, 10.3087100982666, 10.3218297958374
), ps1 = c(5.14855766296387, 4.71904611587524, 7.9462103843689,
10.6017990112305, 11.233078956604, 9.12952136993408, 12.6536712646484,
11.233078956604, 11.233078956604, 11.233078956604, 11.233078956604,
11.233078956604, 5.93759632110596, 10.6017990112305, 11.233078956604,
10.6017990112305, 7.95780467987061, 9.07744884490967, 4.29865598678589,
8.27481746673584, 3.25137901306152, 4.51061344146729, 6.34518480300903,
6.66202449798584, 6.66202449798584, 4.75249433517456, 6.28858852386475,
6.33270215988159, 10.3600759506226, 10.3600759506226, 18.7164611816406,
5.73318386077881, 7.92949104309082, 9.09823608398438, 11.233078956604,
10.4455404281616, 11.233078956604, 10.4455404281616, 10.4455404281616,
10.6017990112305, 9.19112777709961, 10.4455404281616, 11.233078956604,
11.064302444458, 11.233078956604, 5.93759632110596, 11.233078956604,
10.6017990112305, 6.05948448181152, 9.5645227432251), ps2 = c(5.23111915588379,
4.86784505844116, 7.7175760269165, 4.34898376464844, 4.48626232147217,
9.57159423828125, 8.38174915313721, 4.48626232147217, 4.48626232147217,
4.48626232147217, 4.48626232147217, 4.48626232147217, 6.87198734283447,
4.34898376464844, 4.48626232147217, 4.34898376464844, 6.2098217010498,
7.5497522354126, 5.62545442581177, 5.57168531417847, 3.08954334259033,
6.6683931350708, 4.41767883300781, 6.11901044845581, 6.11901044845581,
4.06884765625, 6.35917854309082, 5.7121729850769, 8.55229663848877,
8.55229663848877, 11.8981914520264, 5.49351119995117, 5.34777498245239,
6.12420177459717, 4.48626232147217, 5.2967677116394, 4.48626232147217,
5.2967677116394, 5.2967677116394, 4.34898376464844, 4.51386308670044,
5.2967677116394, 4.48626232147217, 5.98725175857544, 4.48626232147217,
6.87198734283447, 4.48626232147217, 4.34898376464844, 5.58411026000977,
4.42436075210571), ps3 = c(4.95634937286377, 3.50353670120239,
6.01129817962646, 0.851324141025543, 0.816295921802521, 8.03804397583008,
5.56230783462524, 0.816295921802521, 0.816295921802521, 0.816295921802521,
0.816295921802521, 0.816295921802521, 6.01666784286499, 0.851324141025543,
0.816295921802521, 0.851324141025543, 3.45424580574036, 5.31899690628052,
7.45753812789917, 3.34133338928223, 6.61472988128662, 11.244439125061,
2.19617891311646, 5.29748106002808, 5.29748106002808, 1.63307499885559,
5.51272773742676, 6.78562116622925, 4.5334997177124, 4.5334997177124,
4.31791353225708, 7.10963106155396, 2.32198905944824, 2.74845194816589,
0.816295921802521, 1.47570741176605, 0.816295921802521, 1.47570741176605,
1.47570741176605, 0.851324141025543, 1.39068424701691, 1.47570741176605,
0.816295921802521, 1.85064959526062, 0.816295921802521, 6.01666784286499,
0.816295921802521, 0.851324141025543, 6.78009986877441, 1.21070051193237
), ps4 = c(5.66667366027832, 4.82342433929443, 7.40090322494507,
6.59299898147583, 7.33758926391602, 9.98004341125488, 10.3958940505981,
7.33758926391602, 7.33758926391602, 7.33758926391602, 7.33758926391602,
7.33758926391602, 8.31999015808105, 6.59299898147583, 7.33758926391602,
6.59299898147583, 7.05771064758301, 8.38344383239746, 4.75349426269531,
9.00399303436279, 5.48189449310303, 5.9071044921875, 5.30881881713867,
8.68398857116699, 8.68398857116699, 4.32339859008789, 8.57950687408447,
6.78787326812744, 8.68624305725098, 8.68624305725098, 12.9021902084351,
6.14854049682617, 6.71301507949829, 7.50605535507202, 7.33758926391602,
8.11069011688232, 7.33758926391602, 8.11069011688232, 8.11069011688232,
6.59299898147583, 5.92181205749512, 8.11069011688232, 7.33758926391602,
9.29954528808594, 7.33758926391602, 8.31999015808105, 7.33758926391602,
6.59299898147583, 6.16447877883911, 5.83903217315674), ts1 = c(4.19949150085449,
2.46556353569031, 3.96805644035339, 9.05560302734375, 9.5199556350708,
1.18671488761902, 6.60286664962769, 9.5199556350708, 9.5199556350708,
9.5199556350708, 9.5199556350708, 9.5199556350708, 2.12847352027893,
9.05560302734375, 9.5199556350708, 9.05560302734375, 2.11432313919067,
6.49393510818481, -0.165110915899277, 7.78503036499023, -7.71160411834717,
-0.979450941085815, 4.96369075775146, 4.28496122360229, 4.28496122360229,
6.35976600646973, 3.02656149864197, 2.80754446983337, 5.94739389419556,
5.94739389419556, 8.70161914825439, 1.57025468349457, 5.08782005310059,
4.27688789367676, 9.5199556350708, 8.49832916259766, 9.5199556350708,
8.49832916259766, 8.49832916259766, 9.05560302734375, 6.33359289169312,
8.49832916259766, 9.5199556350708, 7.99740839004517, 9.5199556350708,
2.12847352027893, 9.5199556350708, 9.05560302734375, 2.67069268226624,
7.33829879760742), ts2 = c(9.89923763275146, 10.9084701538086,
9.61682415008545, 13.6253662109375, 13.8121919631958, 6.19518041610718,
9.40560817718506, 13.8121919631958, 13.8121919631958, 13.8121919631958,
13.8121919631958, 13.8121919631958, 10.3912172317505, 13.6253662109375,
13.8121919631958, 13.6253662109375, 9.77112770080566, 11.5460777282715,
8.18180465698242, 12.9412984848022, 2.54625177383423, 8.29829216003418,
10.6650953292847, 10.1770324707031, 10.1770324707031, 12.4333782196045,
8.98324680328369, 8.45312309265137, 9.23384857177734, 9.23384857177734,
11.371600151062, 8.09108352661133, 12.0714511871338, 11.385799407959,
13.8121919631958, 13.912787437439, 13.8121919631958, 13.912787437439,
13.912787437439, 13.6253662109375, 12.0018119812012, 13.912787437439,
13.8121919631958, 14.0190010070801, 13.8121919631958, 10.3912172317505,
13.8121919631958, 13.6253662109375, 8.53981018066406, 12.7294788360596
), ts3 = c(17.718994140625, 21.1172523498535, 17.8669090270996,
23.1215572357178, 22.9536685943604, 15.3891229629517, 15.7000684738159,
22.9536685943604, 22.9536685943604, 22.9536685943604, 22.9536685943604,
22.9536685943604, 20.1229286193848, 23.1215572357178, 22.9536685943604,
23.1215572357178, 19.8251171112061, 19.3250198364258, 16.8351039886475,
22.2966594696045, 14.6743259429932, 17.1554985046387, 20.1656894683838,
20.0012702941895, 20.0012702941895, 23.2738876342773, 18.6255321502686,
16.2553405761719, 16.551155090332, 16.551155090332, 17.6266174316406,
16.1711521148682, 22.280725479126, 21.450382232666, 22.9536685943604,
23.5616970062256, 22.9536685943604, 23.5616970062256, 23.5616970062256,
23.1215572357178, 22.1113948822021, 23.5616970062256, 22.9536685943604,
23.5085678100586, 22.9536685943604, 20.1229286193848, 22.9536685943604,
23.1215572357178, 16.3595314025879, 22.7737102508545), ts4 = c(11.661883354187,
12.7669324874878, 11.6320190429688, 17.2357921600342, 17.4911460876465,
9.09537506103516, 12.179615020752, 17.4911460876465, 17.4911460876465,
17.4911460876465, 17.4911460876465, 17.4911460876465, 12.0781927108765,
17.2357921600342, 17.4911460876465, 17.2357921600342, 11.9486837387085,
13.7441387176514, 8.9575023651123, 15.9984045028687, 4.02816677093506,
9.12790489196777, 13.0505475997925, 12.842321395874, 12.842321395874,
14.8937959671021, 11.5566177368164, 10.0515727996826, 12.2921047210693,
12.2921047210693, 14.2251281738281, 9.64802074432373, 14.6072359085083,
13.7993869781494, 17.4911460876465, 17.0232067108154, 17.4911460876465,
17.0232067108154, 17.0232067108154, 17.2357921600342, 15.045259475708,
17.0232067108154, 17.4911460876465, 16.7633666992188, 17.4911460876465,
12.0781927108765, 17.4911460876465, 17.2357921600342, 10.0954942703247,
15.9187803268433), ps1sq = c(26.5076465606689, 22.2693958282471,
63.1422576904297, 112.398139953613, 126.182060241699, 83.3481597900391,
160.11540222168, 126.182060241699, 126.182060241699, 126.182060241699,
126.182060241699, 126.182060241699, 35.2550506591797, 112.398139953613,
126.182060241699, 112.398139953613, 63.3266563415527, 82.4000778198242,
18.478443145752, 68.4726028442383, 10.5714654922485, 20.3456344604492,
40.2613716125488, 44.3825721740723, 44.3825721740723, 22.58620262146,
39.5463447570801, 40.1031150817871, 107.331176757812, 107.331176757812,
350.305908203125, 32.8693962097168, 62.8768272399902, 82.7779006958008,
126.182060241699, 109.109313964844, 126.182060241699, 109.109313964844,
109.109313964844, 112.398139953613, 84.4768295288086, 109.109313964844,
126.182060241699, 122.418785095215, 126.182060241699, 35.2550506591797,
126.182060241699, 112.398139953613, 36.7173538208008, 91.480094909668
), ps2sq = c(27.3646068572998, 23.695915222168, 59.560977935791,
18.9136600494385, 20.1265487670898, 91.6154174804688, 70.2537155151367,
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39.9931793212891, 36.0810203552246, 75.7048721313477, 33.5687866210938
), AT = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), BE = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0), DE = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), DK = c(0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0), ES = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), FI = c(0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0), FR = c(1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), GR = c(0, 1, 0,
1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
0, 1, 1, 0, 1), IE = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), IT = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0), LU = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), NL = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0), PT = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), SE = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), WDE = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), EDE = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), UK = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CY = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), BG = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CZ = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), EE = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), HU = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), LT = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), LV = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), PL = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), RO = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), SI = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), SK = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), b48 = c(70, 2.70000004768372, 63.9000015258789,
5.5, 6.30000019073486, 8.80000019073486, 48.0800018310547, 5.09999990463257,
6.40000009536743, 6, 6.69999980926514, 4, 6.30000019073486, 5.80000019073486,
8.80000019073486, 2, 13, 0.5, 10.25, 34, 65.2300033569336, 37.7799987792969,
74.9400024414062, 31.0200004577637, 20.0300006866455, 70.7200012207031,
40, 4.90000009536743, 13.5, 5, 26.8700008392334, 3, 2, 3.09999990463257,
6.80000019073486, 15.6999998092651, 9.19999980926514, 5.30000019073486,
4.59999990463257, 17.3999996185303, 7, 4.90000009536743, 13.3999996185303,
2.34999990463257, 8.5, 24.8700008392334, 4, 1.39999997615814,
34.7799987792969, 6.69999980926514), b50 = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 34.2400016784668, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), irrigation = c(0, 100, 0, 5.45454584062099,
7.9365074634552, 89.3392562866211, 0, 17.6470592617989, 0, 0,
65.5172407627106, 0, 61.904764175415, 34.4827562570572, 7.95454531908035,
75, 0, 0, 0, 0, 0, 0, 5.26393800973892, 0, 0, 0, 0, 0, 0, 0,
0, 0, 74.6153831481934, 84.6153914928436, 0, 5.09554147720337,
0, 0, 0, 21.0884347558022, 18.4549376368523, 6.1224490404129,
25.3731369972229, 2.12765969336033, 0, 84.3988716602325, 0, 0,
0, 100), awc_class = c(106.228088378906, 78.2306137084961, 80.9311141967773,
32.4921531677246, 54.8475151062012, 80.6665878295898, 116.331588745117,
54.8475151062012, 54.8475151062012, 54.8475151062012, 54.8475151062012,
54.8475151062012, 56.3101806640625, 32.4921531677246, 54.8475151062012,
32.4921531677246, 59.3034172058105, 101.193893432617, 96.5840377807617,
54.2786560058594, 87.1388244628906, 66.1907730102539, 57.205738067627,
55.4114303588867, 55.4114303588867, 80.9288787841797, 63.6008758544922,
150, 30.3404140472412, 30.3404140472412, 19.8318557739258, 104.236854553223,
79.2445755004883, 57.0045547485352, 54.8475151062012, 34.320426940918,
54.8475151062012, 34.320426940918, 34.320426940918, 32.4921531677246,
65.1337509155273, 34.320426940918, 54.8475151062012, 73.6748657226562,
54.8475151062012, 56.3101806640625, 54.8475151062012, 32.4921531677246,
127.726959228516, 27.9528160095215), sys02 = c(18.8571434020996,
303.529418945312, 30.2469139099121, 104.305557250977, 86.4935073852539,
51.25, 83.0927810668945, 453.118286132812, 42.5, 104.305557250977,
48.461540222168, 86.4935073852539, 55.1851844787598, 104.305557250977,
104.305557250977, 185.277770996094, 17.9775276184082, 25.2777786254883,
64, 21.6666660308838, 30, 24.2372875213623, 47.0285720825195,
16.1904754638672, 33.75, 22.5423736572266, 10.2857141494751,
39.230770111084, 6.06741571426392, 1, 28.3255805969238, 21.6000003814697,
69.2592620849609, 86.6666641235352, 48.5185203552246, 44.4186058044434,
48.6538467407227, 437.105255126953, 437.105255126953, 19.1666660308838,
48.461540222168, 437.105255126953, 48.6538467407227, 453.118286132812,
48.6538467407227, 14.2857141494751, 453.118286132812, 453.118286132812,
95.2380981445312, 63), se025 = c(163.529998779297, 2.70000004768372,
157, 5.5, 6.30000019073486, 36.0200004577637, 86, 5.09999990463257,
6.40000009536743, 6, 8.69999980926514, 4, 6.30000019073486, 5.80000019073486,
8.80000019073486, 2, 118.809997558594, 44.1100006103516, 16.7000007629395,
34, 73.4000015258789, 73.0800018310547, 134.880004882812, 31.0200004577637,
20.0300006866455, 94.7200012207031, 40, 5.5, 16.5, 15, 26.8700008392334,
59.4199981689453, 13, 5.19999980926514, 6.80000019073486, 15.6999998092651,
10.8999996185303, 5.30000019073486, 4.59999990463257, 29.3999996185303,
23.2999992370605, 4.90000009536743, 13.3999996185303, 2.34999990463257,
8.5, 24.8700008392334, 4.19999980926514, 1.39999997615814, 34.7799987792969,
6.69999980926514)), .Names = c("LnALVperHA", "ps1", "ps2", "ps3",
"ps4", "ts1", "ts2", "ts3", "ts4", "ps1sq", "ps2sq", "ps3sq",
"ps4sq", "ts1sq", "ts2sq", "ts3sq", "ts4sq", "pdnsty", "portsML",
"cities500k", "rentedland", "subsidies1", "elevmean", "elevrange",
"t_gravel", "t_ph_h2o", "t_silt", "t_sand", "AT", "BE", "DE",
"DK", "ES", "FI", "FR", "GR", "IE", "IT", "LU", "NL", "PT", "SE",
"WDE", "EDE", "UK", "CY", "BG", "CZ", "EE", "HU", "LT", "LV",
"PL", "RO", "SI", "SK", "b48", "b50", "irrigation", "awc_class",
"sys02", "se025"), row.names = c("2", "3", "4", "5", "6", "7",
"8", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20",
"21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31",
"32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42",
"43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53"
), class = "data.frame")



























2015-08-14 14:58 GMT+02:00 PIKAL Petr <petr.pikal at precheza.cz>:
--

Mevrouw Janka Vanschoenwinkel
Doctoraatsbursaal - PhD
Milieueconomie - Environmental economics

T +32(0)11 26 87 42 | GSM +32(0)476 28 21 40

www.uhasselt.be/eec

Universiteit Hasselt | Campus Diepenbeek
Agoralaan Gebouw D | B-3590 Diepenbeek
Kantoor F11

Postadres: Universiteit Hasselt | Martelarenlaan 42 | B-3500 Hasselt

P Please consider the environment before printing this e-mail
#
On Aug 14, 2015, at 6:40 AM, Janka Vanschoenwinkel wrote:

            
When using a function in R you may need to supply an argument name. Are you expecting this to be the number of groups. I cannot decipher the intent here with such sparse commentary, but this call to `cut2` does not make sense to me. Perhaps you meant the number of groups? .... in which case you need  cut2( Alldata$irrigation, g=i ), since the arguments to cut2 are not that same as the arguments to cut.

At the moment you are implicitly sending on the first pass a 1 and then on the second pass a 2 to the second argument of cut2 which is the `breaks` argument. So you wold be getting two different factors each with different cut-point levels. I looked at your data and in point of fact there would be no difference since you have 29 zero values and no values between 0 and 1.
0 [  1,100] 
       29        21
0 [  2,100] 
       29        21
David Winsemius
Alameda, CA, USA
1 day later
#
Hi David,

Thanks for your comment. I'll explain what I want to do. I explained it
already earlier but the explanation might have gone lost in some of the
emails.

The variable irrigation ranges from 0 to 100. (maybe not in de small sample
I gave, but in reality I have over 60000 observations and there the
variable ranges from 0 to 100). I want to make (and use) 100 different
samples. The sample is based each time on the "i" that I put at the
beginning of the loop.

So:

i = 1: this means there are 2 subsets. One from 0-1, another from 1-100
i = 2: this means there are 2 subsets. One from 0-2, another from 2-100
i = 3: this means there are 2 subsets. One from 0-3, another from 3-100
i = 4: this means there are 2 subsets. One from 0-4, another from 4-100
...
i = 96: this means there are 2 subsets. One from 0-96, another from 96-100
i = 97: this means there are 2 subsets. One from 0-97, another from 97-100
i = 98: this means there are 2 subsets. One from 0-98, another from 98-100
i = 99: this means there are 2 subsets. One from 0-99, another from 99-100

It might be possible that i = 1 and i = 2 give the same results in the
small dataset. But in the full dataset all numbers are represented.

The cut2 function is capable of "cutting" a sample based on a number
supplied. Yet, when I tell him this number is "i", then it doesn't work. If
instead I write that the number is 10, then it does work and it gives me 2
subsets from 0-10 and from 10-100.

Hope this is more clear!

Janka


2015-08-14 20:10 GMT+02:00 David Winsemius <dwinsemius at comcast.net>:

  
    
#
On Aug 16, 2015, at 8:57 AM, Janka VANSCHOENWINKEL wrote:

            
I now see that you did explain that you wanted the positional matching in cut2 as a "break". The code runs without error on my machine, but delivers a lot of warnings about masking. You are repeatedly using attach on the same named objects. Using `attach` in programming is generally not a good idea. In interactive use it is safer to use `with`, although that is not generally considered safe in programming, either.

You need to do a better job of nailing down the source of the difficulty what ever it might be. While you say the cut2 function "doesn't work", you don't actually give evidence of "failure".

It's fairly simple to show that your theory about why your code fails in some way as being due to cut2 failing to accept an "i" value inside an lapply call is just wrong:
[[1]]
 [1]  0      [ 1,10] [ 1,10] [ 1,10] [ 1,10] [ 1,10] [ 1,10]
 [8] [ 1,10] [ 1,10] [ 1,10] [ 1,10]
Levels:  0 [ 1,10]

[[2]]
 [1] [ 0, 2) [ 0, 2) [ 2,10] [ 2,10] [ 2,10] [ 2,10] [ 2,10]
 [8] [ 2,10] [ 2,10] [ 2,10] [ 2,10]
Levels: [ 0, 2) [ 2,10]

[[3]]
 [1] [ 0, 3) [ 0, 3) [ 0, 3) [ 3,10] [ 3,10] [ 3,10] [ 3,10]
 [8] [ 3,10] [ 3,10] [ 3,10] [ 3,10]
Levels: [ 0, 3) [ 3,10]


You also have two different definitions of weight2 for your irrigation model:

Alldata_Irrigation$weight2<-Alldata_Irrigation$sys02*Alldata_Irrigation$se025
Alldata_Irrigation$weight2<-Alldata_Irrigation$b48+Alldata_Irrigation$b50
6 days later
#
Thank you all very much. A combination of the solutions suggested solved my
problem!

2015-08-16 22:31 GMT+02:00 David Winsemius <dwinsemius at comcast.net>: