Unexpected output containing plus, minus, and letters produced by subtracting one column of numbers from another in R










0














I have a data.frame containing a vector of numeric values (prcp_log).



 waterdate PRCP prcp_log
<date> <dbl> <dbl>
1 2007-10-01 0 0
2 2007-10-02 0.02 0.0198
3 2007-10-03 0.31 0.270
4 2007-10-04 1.8 1.03
5 2007-10-05 0.03 0.0296
6 2007-10-06 0.19 0.174


I then pass this data through Christiano-Fitzgerald band pass filter using the following command from the mfilter package.



library(mFilter)

US1ORLA0076_cffilter <- cffilter(US1ORLA0076$prcp_log,pl=180,pu=365,root=FALSE,drift=FALSE,
type=c("asymmetric"),
nfix=NULL,theta=1)


Which creates an S3 object containing, among other things, and vector of "trend" values and a vector of "cycle" values, like so:



head(US1ORLA0076_cffilter$trend)
[,1]
[1,] 0.05439408
[2,] 0.07275321
[3,] 0.32150292
[4,] 1.07958965
[5,] 0.07799329
[6,] 0.22082246

head(US1ORLA0076_cffilter$cycle)
[,1]
[1,] -0.05439408
[2,] -0.05295058
[3,] -0.05147578
[4,] -0.04997023
[5,] -0.04843449
[6,] -0.04686915


Plotted:



plot(US1ORLA0076_cffilter)


enter image description here



I then apply the following mathematical operation in attempt to remove the trend and seasonal components from the original numeric vector:



US1ORLA0076$decomp <- ((US1ORLA0076$prcp_log - US1ORLA0076_cffilter$trend) - US1ORLA0076_cffilter$cycle)


Which creates an output of values which includes unexpected elements such as dashes and letters.



head(US1ORLA0076$decomp)
[,1]
[1,] 0.000000e+00
[2,] 0.000000e+00
[3,] 1.387779e-17
[4,] -2.775558e-17
[5,] 0.000000e+00
[6,] 6.938894e-18


What has happened here? What do these additional characters signify? How can perform this mathematical operation and achieve the desired output of simply $log_prcp minus both the $tend and $cycle values?



I am happy to provide any additional info that will help right away, just ask.










share|improve this question



















  • 1




    This is scientific notation. To turn it off use options(scipen = 999)
    – Harro Cyranka
    Nov 12 '18 at 20:12






  • 1




    Are you referring to the "e-" and "e+"? They are the exponent form. You can take it to mean "10 to the power of"
    – SmitM
    Nov 12 '18 at 20:13











  • Is the meaning and usage of this notation in R documented somewhere where I can read more about it? What is it called / what should I search for? @HarroCyranka
    – Clayton Glasser
    Nov 12 '18 at 20:19










  • These decomp figures are so tiny that I suspect your filter is overfitting and your trend is capturing the signal AND the noise, so that there's only a floating point rounding error left, in the 17th or 18th decimal place.
    – Jon Spring
    Nov 12 '18 at 20:19







  • 1




    I found this website that may be valuable: burns-stat.com/documents/tutorials/impatient-r/…
    – Harro Cyranka
    Nov 12 '18 at 20:29
















0














I have a data.frame containing a vector of numeric values (prcp_log).



 waterdate PRCP prcp_log
<date> <dbl> <dbl>
1 2007-10-01 0 0
2 2007-10-02 0.02 0.0198
3 2007-10-03 0.31 0.270
4 2007-10-04 1.8 1.03
5 2007-10-05 0.03 0.0296
6 2007-10-06 0.19 0.174


I then pass this data through Christiano-Fitzgerald band pass filter using the following command from the mfilter package.



library(mFilter)

US1ORLA0076_cffilter <- cffilter(US1ORLA0076$prcp_log,pl=180,pu=365,root=FALSE,drift=FALSE,
type=c("asymmetric"),
nfix=NULL,theta=1)


Which creates an S3 object containing, among other things, and vector of "trend" values and a vector of "cycle" values, like so:



head(US1ORLA0076_cffilter$trend)
[,1]
[1,] 0.05439408
[2,] 0.07275321
[3,] 0.32150292
[4,] 1.07958965
[5,] 0.07799329
[6,] 0.22082246

head(US1ORLA0076_cffilter$cycle)
[,1]
[1,] -0.05439408
[2,] -0.05295058
[3,] -0.05147578
[4,] -0.04997023
[5,] -0.04843449
[6,] -0.04686915


Plotted:



plot(US1ORLA0076_cffilter)


enter image description here



I then apply the following mathematical operation in attempt to remove the trend and seasonal components from the original numeric vector:



US1ORLA0076$decomp <- ((US1ORLA0076$prcp_log - US1ORLA0076_cffilter$trend) - US1ORLA0076_cffilter$cycle)


Which creates an output of values which includes unexpected elements such as dashes and letters.



head(US1ORLA0076$decomp)
[,1]
[1,] 0.000000e+00
[2,] 0.000000e+00
[3,] 1.387779e-17
[4,] -2.775558e-17
[5,] 0.000000e+00
[6,] 6.938894e-18


What has happened here? What do these additional characters signify? How can perform this mathematical operation and achieve the desired output of simply $log_prcp minus both the $tend and $cycle values?



I am happy to provide any additional info that will help right away, just ask.










share|improve this question



















  • 1




    This is scientific notation. To turn it off use options(scipen = 999)
    – Harro Cyranka
    Nov 12 '18 at 20:12






  • 1




    Are you referring to the "e-" and "e+"? They are the exponent form. You can take it to mean "10 to the power of"
    – SmitM
    Nov 12 '18 at 20:13











  • Is the meaning and usage of this notation in R documented somewhere where I can read more about it? What is it called / what should I search for? @HarroCyranka
    – Clayton Glasser
    Nov 12 '18 at 20:19










  • These decomp figures are so tiny that I suspect your filter is overfitting and your trend is capturing the signal AND the noise, so that there's only a floating point rounding error left, in the 17th or 18th decimal place.
    – Jon Spring
    Nov 12 '18 at 20:19







  • 1




    I found this website that may be valuable: burns-stat.com/documents/tutorials/impatient-r/…
    – Harro Cyranka
    Nov 12 '18 at 20:29














0












0








0







I have a data.frame containing a vector of numeric values (prcp_log).



 waterdate PRCP prcp_log
<date> <dbl> <dbl>
1 2007-10-01 0 0
2 2007-10-02 0.02 0.0198
3 2007-10-03 0.31 0.270
4 2007-10-04 1.8 1.03
5 2007-10-05 0.03 0.0296
6 2007-10-06 0.19 0.174


I then pass this data through Christiano-Fitzgerald band pass filter using the following command from the mfilter package.



library(mFilter)

US1ORLA0076_cffilter <- cffilter(US1ORLA0076$prcp_log,pl=180,pu=365,root=FALSE,drift=FALSE,
type=c("asymmetric"),
nfix=NULL,theta=1)


Which creates an S3 object containing, among other things, and vector of "trend" values and a vector of "cycle" values, like so:



head(US1ORLA0076_cffilter$trend)
[,1]
[1,] 0.05439408
[2,] 0.07275321
[3,] 0.32150292
[4,] 1.07958965
[5,] 0.07799329
[6,] 0.22082246

head(US1ORLA0076_cffilter$cycle)
[,1]
[1,] -0.05439408
[2,] -0.05295058
[3,] -0.05147578
[4,] -0.04997023
[5,] -0.04843449
[6,] -0.04686915


Plotted:



plot(US1ORLA0076_cffilter)


enter image description here



I then apply the following mathematical operation in attempt to remove the trend and seasonal components from the original numeric vector:



US1ORLA0076$decomp <- ((US1ORLA0076$prcp_log - US1ORLA0076_cffilter$trend) - US1ORLA0076_cffilter$cycle)


Which creates an output of values which includes unexpected elements such as dashes and letters.



head(US1ORLA0076$decomp)
[,1]
[1,] 0.000000e+00
[2,] 0.000000e+00
[3,] 1.387779e-17
[4,] -2.775558e-17
[5,] 0.000000e+00
[6,] 6.938894e-18


What has happened here? What do these additional characters signify? How can perform this mathematical operation and achieve the desired output of simply $log_prcp minus both the $tend and $cycle values?



I am happy to provide any additional info that will help right away, just ask.










share|improve this question















I have a data.frame containing a vector of numeric values (prcp_log).



 waterdate PRCP prcp_log
<date> <dbl> <dbl>
1 2007-10-01 0 0
2 2007-10-02 0.02 0.0198
3 2007-10-03 0.31 0.270
4 2007-10-04 1.8 1.03
5 2007-10-05 0.03 0.0296
6 2007-10-06 0.19 0.174


I then pass this data through Christiano-Fitzgerald band pass filter using the following command from the mfilter package.



library(mFilter)

US1ORLA0076_cffilter <- cffilter(US1ORLA0076$prcp_log,pl=180,pu=365,root=FALSE,drift=FALSE,
type=c("asymmetric"),
nfix=NULL,theta=1)


Which creates an S3 object containing, among other things, and vector of "trend" values and a vector of "cycle" values, like so:



head(US1ORLA0076_cffilter$trend)
[,1]
[1,] 0.05439408
[2,] 0.07275321
[3,] 0.32150292
[4,] 1.07958965
[5,] 0.07799329
[6,] 0.22082246

head(US1ORLA0076_cffilter$cycle)
[,1]
[1,] -0.05439408
[2,] -0.05295058
[3,] -0.05147578
[4,] -0.04997023
[5,] -0.04843449
[6,] -0.04686915


Plotted:



plot(US1ORLA0076_cffilter)


enter image description here



I then apply the following mathematical operation in attempt to remove the trend and seasonal components from the original numeric vector:



US1ORLA0076$decomp <- ((US1ORLA0076$prcp_log - US1ORLA0076_cffilter$trend) - US1ORLA0076_cffilter$cycle)


Which creates an output of values which includes unexpected elements such as dashes and letters.



head(US1ORLA0076$decomp)
[,1]
[1,] 0.000000e+00
[2,] 0.000000e+00
[3,] 1.387779e-17
[4,] -2.775558e-17
[5,] 0.000000e+00
[6,] 6.938894e-18


What has happened here? What do these additional characters signify? How can perform this mathematical operation and achieve the desired output of simply $log_prcp minus both the $tend and $cycle values?



I am happy to provide any additional info that will help right away, just ask.







r subtraction bandpass-filter






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 12 '18 at 20:53

























asked Nov 12 '18 at 20:08









Clayton Glasser

518




518







  • 1




    This is scientific notation. To turn it off use options(scipen = 999)
    – Harro Cyranka
    Nov 12 '18 at 20:12






  • 1




    Are you referring to the "e-" and "e+"? They are the exponent form. You can take it to mean "10 to the power of"
    – SmitM
    Nov 12 '18 at 20:13











  • Is the meaning and usage of this notation in R documented somewhere where I can read more about it? What is it called / what should I search for? @HarroCyranka
    – Clayton Glasser
    Nov 12 '18 at 20:19










  • These decomp figures are so tiny that I suspect your filter is overfitting and your trend is capturing the signal AND the noise, so that there's only a floating point rounding error left, in the 17th or 18th decimal place.
    – Jon Spring
    Nov 12 '18 at 20:19







  • 1




    I found this website that may be valuable: burns-stat.com/documents/tutorials/impatient-r/…
    – Harro Cyranka
    Nov 12 '18 at 20:29













  • 1




    This is scientific notation. To turn it off use options(scipen = 999)
    – Harro Cyranka
    Nov 12 '18 at 20:12






  • 1




    Are you referring to the "e-" and "e+"? They are the exponent form. You can take it to mean "10 to the power of"
    – SmitM
    Nov 12 '18 at 20:13











  • Is the meaning and usage of this notation in R documented somewhere where I can read more about it? What is it called / what should I search for? @HarroCyranka
    – Clayton Glasser
    Nov 12 '18 at 20:19










  • These decomp figures are so tiny that I suspect your filter is overfitting and your trend is capturing the signal AND the noise, so that there's only a floating point rounding error left, in the 17th or 18th decimal place.
    – Jon Spring
    Nov 12 '18 at 20:19







  • 1




    I found this website that may be valuable: burns-stat.com/documents/tutorials/impatient-r/…
    – Harro Cyranka
    Nov 12 '18 at 20:29








1




1




This is scientific notation. To turn it off use options(scipen = 999)
– Harro Cyranka
Nov 12 '18 at 20:12




This is scientific notation. To turn it off use options(scipen = 999)
– Harro Cyranka
Nov 12 '18 at 20:12




1




1




Are you referring to the "e-" and "e+"? They are the exponent form. You can take it to mean "10 to the power of"
– SmitM
Nov 12 '18 at 20:13





Are you referring to the "e-" and "e+"? They are the exponent form. You can take it to mean "10 to the power of"
– SmitM
Nov 12 '18 at 20:13













Is the meaning and usage of this notation in R documented somewhere where I can read more about it? What is it called / what should I search for? @HarroCyranka
– Clayton Glasser
Nov 12 '18 at 20:19




Is the meaning and usage of this notation in R documented somewhere where I can read more about it? What is it called / what should I search for? @HarroCyranka
– Clayton Glasser
Nov 12 '18 at 20:19












These decomp figures are so tiny that I suspect your filter is overfitting and your trend is capturing the signal AND the noise, so that there's only a floating point rounding error left, in the 17th or 18th decimal place.
– Jon Spring
Nov 12 '18 at 20:19





These decomp figures are so tiny that I suspect your filter is overfitting and your trend is capturing the signal AND the noise, so that there's only a floating point rounding error left, in the 17th or 18th decimal place.
– Jon Spring
Nov 12 '18 at 20:19





1




1




I found this website that may be valuable: burns-stat.com/documents/tutorials/impatient-r/…
– Harro Cyranka
Nov 12 '18 at 20:29





I found this website that may be valuable: burns-stat.com/documents/tutorials/impatient-r/…
– Harro Cyranka
Nov 12 '18 at 20:29













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