Hi,
One more thing,
ydat1: original dataset
ydat2<-data.frame(ydat1)
#Not sure ,how you did this step on original data because::
dframe<- data.frame(Dcre1=DCred1[1:21],Dcre2=DCred2[1:21],Dcre3=DCred3[1:21],
Dbobc2=DBoBC2[1:21],Dbobc3=DBoBC3[1:21],CredL=CredL1[1:21],BoBCL=BoBCL1[1:21])
I am getting errors for that step, when I used ydat1.
head(ydat1)
[1] 68.1 -34.8 90.4 54.6 -172.3 51.8
head(ydat2)
DCred1 DCred2 DCred3 DBoBC2 DBoBC3 CredL1 BoBCL1
1 68.1 NA NA NA NA 4937.0 4187.500
2 -34.8 -102.9 NA -164.45784 NA 5005.1 4296.005
3 90.4 125.2 228.1 17.07935 181.53719 4970.3 4240.052
4 54.6 -35.8 -161.0 95.97679 78.89743 5060.7 4201.178
5 -172.3 -226.9 -191.1 680.23817 584.26138 5115.3 4258.281
6 51.8 224.1 451.0 -491.34869 -1171.58686 4943.0 4995.623
#I analyzed [1:21] again in ydat2.
dframe<-data.frame(Dcre1=ydat2$DCred1[1:21],Dcre2=ydat2$DCred2[1:21],Dcre3=ydat2$DCred3[1:21],Dbobc2=ydat2$DBoBC2[1:21],Dbobc3=ydat2$DBoBC3[1:21],CredL=ydat2$CredL1[1:21],BoBCL=ydat2$BoBCL1[1:21])
But, the results are bit different than in my earlier post, because, here the
NAs are still present in different rows. So, the observations in those rows
will be deleted while it is analyzed.
regCred<- lm(Dcre1~Dcre2+Dcre3+Dbobc2+Dbobc3+CredL+BoBCL, data=dframe)
> summary(regCred)
Call:
lm(formula = Dcre1 ~ Dcre2 + Dcre3 + Dbobc2 + Dbobc3 + CredL +
BoBCL, data = dframe)
Residuals:
Min 1Q Median 3Q Max
-118.687 -25.568 -5.334 35.035 69.992
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -485.42427 209.47952 -2.317 0.038958 *
Dcre2 0.95097 0.18156 5.238 0.000209 ***
Dcre3 -0.28676 0.10787 -2.658 0.020852 *
Dbobc2 -0.09512 0.09334 -1.019 0.328278
Dbobc3 0.03199 0.04933 0.648 0.528936
CredL 0.14825 0.07193 2.061 0.061645 .
BoBCL -0.04844 0.04333 -1.118 0.285540
---
A.K.
________________________________
From: "Lekgatlhamang, lexi Setlhare" <lexisetlh...@yahoo.com>
To: arun <smartpink...@yahoo.com>
Cc: R help <r-help@r-project.org>
Sent: Monday, July 2, 2012 11:43 AM
Subject: Re: [R] Adjusting length of series
Thanks very much A.K. I have to admit that my problem was not clearly stated,
with the structure of my data provided. Now all is well.
Cheers
Lexi
From: arun <smartpink...@yahoo.com>
To: "Lekgatlhamang, lexi Setlhare" <lexisetlh...@yahoo.com>
Cc: R help <r-help@r-project.org>
Sent: Monday, July 2, 2012 4:40 PM
Subject: Re: [R] Adjusting length of series
Hello,
The class of your data is not dataframe.
Suppose I call your data as ydat1
str(ydat1)
mts [1:24, 1:7] 68.1 -34.8 90.4 54.6 -172.3 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:7] "DCred1" "DCred2" "DCred3" "DBoBC2" ...
- attr(*, "tsp")= num [1:3] 2001 2003 12
- attr(*, "class")= chr [1:2] "mts" "ts"
ydat2<-data.frame(ydat1)
str(ydat2)
'data.frame': 24 obs. of 7 variables:
$ DCred1: num 68.1 -34.8 90.4 54.6 -172.3 ...
$ DCred2: num NA -102.9 125.2 -35.8 -226.9 ...
$ DCred3: num NA NA 228 -161 -191 ...
$ DBoBC2: num NA -164.5 17.1 96 680.2 ...
$ DBoBC3: num NA NA 181.5 78.9 584.3 ...
$ CredL1: num 4937 5005 4970 5061 5115 ...
$ BoBCL1: num 4188 4296 4240 4201 4258 ...
#Since you wanted only to do lm
for these columns, I guess it doesn't really matter whether you have month and
year in the dataset.
#With NAs
regCred<-lm(DCred1~DCred2+DCred3+DBoBC2+DBoBC3+CredL1+BoBCL1,data=ydat2)
> summary(regCred)
Call:
lm(formula = DCred1 ~ DCred2 + DCred3 + DBoBC2 + DBoBC3 + CredL1 +
BoBCL1, data = ydat2)
Residuals:
Min 1Q Median 3Q Max
-124.988463 -33.133975 7.971083 23.607953 76.813601
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)
-538.61375718 205.91179535 -2.61575 0.020344 *
DCred2 0.96401908 0.15623660 6.17025 2.4337e-05 ***
DCred3 -0.25720355 0.08983607 -2.86303 0.012524 *
DBoBC2 -0.11222347 0.07828182 -1.43358 0.173646
DBoBC3 0.04564621 0.03825169 1.19331 0.252578
CredL1 0.18499925 0.06565456 2.81777 0.013693 *
BoBCL1 -0.07682710 0.03406916 -2.25503 0.040666 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01
‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 54.44479 on 14 degrees of freedom
(3 observations deleted due to missingness)
Multiple R-squared: 0.9324472, Adjusted R-squared: 0.903496
F-statistic: 32.20757 on 6 and 14 DF, p-value: 2.046024e-07
Without NAs
> ydat3<-na.omit(ydat2)
> regCred<-lm(DCred1~DCred2+DCred3+DBoBC2+DBoBC3+CredL1+BoBCL1,data=ydat3)
> summary(regCred)
Call:
lm(formula = DCred1 ~ DCred2 + DCred3 + DBoBC2 + DBoBC3 + CredL1 +
BoBCL1, data = ydat3)
Residuals:
Min 1Q Median 3Q Max
-124.988463 -33.133975 7.971083 23.607953 76.813601
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -538.61375718 205.91179535 -2.61575 0.020344 *
DCred2 0.96401908 0.15623660 6.17025 2.4337e-05 ***
DCred3 -0.25720355 0.08983607 -2.86303 0.012524 *
DBoBC2 -0.11222347 0.07828182 -1.43358 0.173646
DBoBC3 0.04564621 0.03825169 1.19331 0.252578
CredL1 0.18499925 0.06565456
2.81777 0.013693 *
BoBCL1 -0.07682710 0.03406916 -2.25503 0.040666 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 54.44479 on 14 degrees of freedom
Multiple R-squared: 0.9324472, Adjusted R-squared: 0.903496
F-statistic: 32.20757 on 6 and 14 DF, p-value: 2.046024e-
#Same result
Not sure what you meant by ("This is good, but couldn't I code the process for
my 15 variable model?")
A.K.
________________________________
From: "Lekgatlhamang, lexi Setlhare" <lexisetlh...@yahoo.com>
To: arun <smartpink...@yahoo.com>
Cc: R help
<r-help@r-project.org>
Sent: Monday, July 2, 2012 5:13 AM
Subject: Re: [R] Adjusting length of series
Hi David and AK,
I have been trying to implement your suggestions since yesterday, but I
encountered some challenges.
As for David's suggestions, I could only implement it after some
modifications. Using an abridged version of my data, I dpud my dataset and then
show my steps below.
> dput(ydata)
structure(c(68.1000000000004, -34.8000000000002, 90.3999999999996,
54.6000000000004, -172.3, 51.8000000000002, 175, 79.8000000000002,
-35.7000000000007, 130.5, 116.8, -67.5, 164.5, 514.8, -326.1,
98.4000000000005, 160.2, 53.1999999999998, 283.6, -111.6, 127.8,
-17.3000000000002, 286.3, NA, NA, -102.900000000001, 125.2, -35.7999999999993,
-226.900000000001, 224.1, 123.2,
-95.1999999999998,
-115.500000000001,
166.200000000001, -13.6999999999998, -184.3, 232, 350.3, -840.900000000001,
424.500000000001, 61.7999999999993, -107, 230.400000000001, -395.200000000001,
239.400000000001, -145.1, 303.6, NA, NA, NA, 228.1, -160.999999999999,
-191.100000000001, 451.000000000001, -100.900000000001, -218.4,
-20.3000000000011, 281.700000000002, -179.900000000001, -170.6,
416.3, 118.3, -1191.2, 1265.4, -362.700000000002, -168.799999999999,
337.400000000001, -625.600000000001, 634.600000000001, -384.500000000001,
448.700000000001, NA, NA, -164.457840999999, 17.0793539999995,
95.9767880000009, 680.238166999999, -491.348690999999, -274.694009,
-256.332907, 469.62296, -146.431891, -41.0772019999995, -106.970104,
757.688263999999, -1689.214533, 2320.098952, -1446.97942, 516.384521,
-375.277650999999, 293.867029999999, 417.845195, 278.198807,
-968.592033999999, -314.195986, NA, NA, NA,
181.537194999999,
78.8974340000013, 584.261378999998, -1171.586858, 216.654681999999,
18.3611019999998, 725.955867, -616.054851, 105.354689000001,
-65.8929020000005, 864.658367999999, -2446.902797, 4009.313485,
-3767.078372, 1963.363941, -891.662171999999, 669.144680999999,
123.978165, -139.646388, -1246.790841, 654.396048, NA, 4937,
5005.1, 4970.3, 5060.7, 5115.3, 4943, 4994.8, 5169.8, 5249.6,
5213.9, 5344.4, 5461.2, 5393.7, 5558.2, 6073, 5746.9, 5845.3,
6005.5, 6058.7, 6342.3, 6230.7, 6358.5, 6341.2, 6627.5, 4187.5,
4296.004835, 4240.051829, 4201.178177, 4258.281313, 4995.622616,
5241.615228, 5212.913831, 4927.879527, 5112.468183, 5150.624948,
5147.704511, 5037.81397, 5685.611693, 4644.194883, 5922.877025,
5754.579747, 6102.66699, 6075.476582, 6342.153204, 7026.675021,
7989.395645, 7983.524235, 7663.456839), .Dim = c(24L, 7L), .Dimnames = list(
NULL, c("DCred1", "DCred2",
"DCred3", "DBoBC2",
"DBoBC3",
"CredL1", "BoBCL1")), .Tsp = c(2001.08333333333, 2003, 12
), class = c("mts", "ts"))
NB: the NAs in the dataset emanated from lagging or differencing the series
David's suggestion
df<-data.frame(DCred1,DCred2,DCred3,DBoBC2,DBoBC3,CredL1,BoBCL1)
Error in data.frame(DCred1, DCred2, DCred3, DBoBC2, DBoBC3, CredL1, BoBCL1) :
arguments imply differing number of rows: 23, 22, 21, 24
So I modified as follows:
length(DCred3) # finding the minimum length of various series
[1] 21
# Then dataframe construction
dframe<- data.frame(Dcre1=DCred1[1:21],Dcre2=DCred2[1:21],Dcre3=DCred3[1:21],
+ Dbobc2=DBoBC2[1:21],Dbobc3=DBoBC3[1:21],CredL=CredL1[1:21],BoBCL=BoBCL1[1:21])
# Then estimated regression
> regCred<- lm(Dcre1~Dcre2+Dcre3+Dbobc2+Dbobc3+CredL+BoBCL, data=dframe)
> summary(regCred)
# Worked well as shown by results
below
Call:
lm(formula = Dcre1 ~ Dcre2 + Dcre3 + Dbobc2 + Dbobc3 + CredL +
BoBCL, data = dframe)
Residuals:
Min 1Q Median 3Q Max
-69.516 -27.695 -8.085 13.851 107.276
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 159.32304 157.15209 1.014 0.327873
Dcre2 -0.75527 0.17262 -4.375 0.000634 ***
Dcre3 -0.21006 0.08656 -2.427 0.029329 *
Dbobc2 0.05111 0.06565 0.779 0.449197
Dbobc3 0.03106 0.03510 0.885 0.391108
CredL -0.10967 0.04933 -2.223 0.043177 *
BoBCL 0.09756 0.03097 3.150 0.007087 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 52.3 on 14 degrees of freedom
Multiple R-squared: 0.9331, Adjusted R-squared: 0.9044
F-statistic: 32.55 on 6 and 14 DF, p-value: 1.911e-07
This is good, but couldn't I code the process for my 15 variable model?
Perhaps that is where the use of
Dcr<- lapply(..., function(x) ...)
comes in?
AK, if you spare some minutes, please use my dput data to illustrate the
suggestion you made, I searched the
lapply function (using ??lapply) but could not get a handle of how to use it in
my case. My dput data is as shown below.
DCred1 DCred2 DCred3 DBoBC2 DBoBC3 CredL1 BoBCL1
Feb 2001 68.1 NA NA NA NA 4937.0 4187.500
Mar 2001 -34.8 -102.9 NA -164.45784 NA 5005.1 4296.005
Apr 2001 90.4 125.2
228.1 17.07935 181.53719 4970.3 4240.052
May 2001 54.6 -35.8 -161.0 95.97679 78.89743 5060.7 4201.178
Jun 2001 -172.3 -226.9
-191.1 680.23817 584.26138 5115.3 4258.281
Jul 2001 51.8 224.1 451.0 -491.34869 -1171.58686 4943.0 4995.623
Aug 2001 175.0 123.2 -100.9 -274.69401 216.65468 4994.8 5241.615
Sep 2001 79.8 -95.2 -218.4 -256.33291 18.36110 5169.8 5212.914
Oct 2001 -35.7 -115.5 -20.3 469.62296 725.95587 5249.6 4927.880
Nov 2001 130.5 166.2 281.7 -146.43189 -616.05485 5213.9 5112.468
Dec 2001 116.8 -13.7 -179.9 -41.07720 105.35469 5344.4 5150.625
Jan 2002 -67.5
-184.3 -170.6 -106.97010 -65.89290 5461.2 5147.705
Feb 2002 164.5 232.0 416.3 757.68826 864.65837 5393.7 5037.814
Mar 2002 514.8
350.3 118.3 -1689.21453 -2446.90280 5558.2 5685.612
Apr 2002 -326.1 -840.9 -1191.2 2320.09895 4009.31348 6073.0 4644.195
May 2002 98.4 424.5 1265.4 -1446.97942 -3767.07837 5746.9 5922.877
Jun 2002 160.2 61.8 -362.7 516.38452 1963.36394 5845.3 5754.580
Jul 2002 53.2 -107.0 -168.8 -375.27765 -891.66217 6005.5 6102.667
Aug 2002 283.6 230.4 337.4 293.86703 669.14468 6058.7 6075.477
Sep 2002 -111.6 -395.2 -625.6 417.84519 123.97817 6342.3 6342.153
Oct 2002 127.8 239.4 634.6 278.19881
-139.64639 6230.7 7026.675
Nov 2002 -17.3 -145.1 -384.5 -968.59203 -1246.79084 6358.5 7989.396
Dec 2002 286.3 303.6 448.7 -314.19599 654.39605 6341.2
7983.524
Jan 2003 NA NA NA NA NA 6627.5 7663.457
Thanks kindly. Lexi
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