How to plot studentized residuals and fitted values in R using ggplot?
0
First, I fitted the model from my data in clean_sales and passed it on an object fit_num_var, but then I had difficulty making it into a plot to visualize the fitted values and the studentized residuals. My code is below:
#Outliers
attach(clean_sales)
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet)
fit_num_var
ggplot(fit_num_var, aes(x=as.vector(fitted.values), y=as.vector(residuals))) +
geom_point() + geom_line() + xlab("Fitted Values") + ylab("Studentized Residuals")
The error message was:
Error in as.vector(x, mode) : cannot coerce type 'closure' to vector of type 'any'
Please let me know how I should fix this. Thanks a lot!
r ggplot2 outliers
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
add a comment |
0
First, I fitted the model from my data in clean_sales and passed it on an object fit_num_var, but then I had difficulty making it into a plot to visualize the fitted values and the studentized residuals. My code is below:
#Outliers
attach(clean_sales)
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet)
fit_num_var
ggplot(fit_num_var, aes(x=as.vector(fitted.values), y=as.vector(residuals))) +
geom_point() + geom_line() + xlab("Fitted Values") + ylab("Studentized Residuals")
The error message was:
Error in as.vector(x, mode) : cannot coerce type 'closure' to vector of type 'any'
Please let me know how I should fix this. Thanks a lot!
r ggplot2 outliers
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
Welcome to Stack Overflow! Could you make your problem reproducible by sharing a sample of your data so others can help (please do not usestr(),head()or screenshot)? You can use thereprexanddatapastapackages to assist you with that. See also Help me Help you & How to make a great R reproducible example?
– Tung
Nov 14 '18 at 16:13
add a comment |
0
0
0
First, I fitted the model from my data in clean_sales and passed it on an object fit_num_var, but then I had difficulty making it into a plot to visualize the fitted values and the studentized residuals. My code is below:
#Outliers
attach(clean_sales)
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet)
fit_num_var
ggplot(fit_num_var, aes(x=as.vector(fitted.values), y=as.vector(residuals))) +
geom_point() + geom_line() + xlab("Fitted Values") + ylab("Studentized Residuals")
The error message was:
Error in as.vector(x, mode) : cannot coerce type 'closure' to vector of type 'any'
Please let me know how I should fix this. Thanks a lot!
r ggplot2 outliers
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
First, I fitted the model from my data in clean_sales and passed it on an object fit_num_var, but then I had difficulty making it into a plot to visualize the fitted values and the studentized residuals. My code is below:
#Outliers
attach(clean_sales)
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet)
fit_num_var
ggplot(fit_num_var, aes(x=as.vector(fitted.values), y=as.vector(residuals))) +
geom_point() + geom_line() + xlab("Fitted Values") + ylab("Studentized Residuals")
The error message was:
Error in as.vector(x, mode) : cannot coerce type 'closure' to vector of type 'any'
Please let me know how I should fix this. Thanks a lot!
r ggplot2 outliers
r ggplot2 outliers
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
asked Nov 14 '18 at 14:57
Vy NguyenVy Nguyen
12
12
Welcome to Stack Overflow! Could you make your problem reproducible by sharing a sample of your data so others can help (please do not usestr(),head()or screenshot)? You can use thereprexanddatapastapackages to assist you with that. See also Help me Help you & How to make a great R reproducible example?
– Tung
Nov 14 '18 at 16:13
add a comment |
Welcome to Stack Overflow! Could you make your problem reproducible by sharing a sample of your data so others can help (please do not usestr(),head()or screenshot)? You can use thereprexanddatapastapackages to assist you with that. See also Help me Help you & How to make a great R reproducible example?
– Tung
Nov 14 '18 at 16:13
Welcome to Stack Overflow! Could you make your problem reproducible by sharing a sample of your data so others can help (please do not use
str(), head() or screenshot)? You can use the reprex and datapasta packages to assist you with that. See also Help me Help you & How to make a great R reproducible example?– Tung
Nov 14 '18 at 16:13
Welcome to Stack Overflow! Could you make your problem reproducible by sharing a sample of your data so others can help (please do not use
str(), head() or screenshot)? You can use the reprex and datapasta packages to assist you with that. See also Help me Help you & How to make a great R reproducible example?– Tung
Nov 14 '18 at 16:13
add a comment |
1 Answer
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No reproducible example, but try this:
- don't use
attach(), use thedata=argument tolm()instead (this isn't your actual problem, but is better practice) - use
fitted(fit_num_var), etc. - you might also be interested in the
augmentfunction from thebroompackage
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet,
data=clean_sales)
ggplot(fit_num_var, aes(x=fitted(fit_num_var),
y=residuals(fit_num_var)) +
geom_point() + smooth() + xlab("Fitted Values") +
ylab("Studentized Residuals")
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
add a comment |
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active
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0
No reproducible example, but try this:
- don't use
attach(), use thedata=argument tolm()instead (this isn't your actual problem, but is better practice) - use
fitted(fit_num_var), etc. - you might also be interested in the
augmentfunction from thebroompackage
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet,
data=clean_sales)
ggplot(fit_num_var, aes(x=fitted(fit_num_var),
y=residuals(fit_num_var)) +
geom_point() + smooth() + xlab("Fitted Values") +
ylab("Studentized Residuals")
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
add a comment |
0
No reproducible example, but try this:
- don't use
attach(), use thedata=argument tolm()instead (this isn't your actual problem, but is better practice) - use
fitted(fit_num_var), etc. - you might also be interested in the
augmentfunction from thebroompackage
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet,
data=clean_sales)
ggplot(fit_num_var, aes(x=fitted(fit_num_var),
y=residuals(fit_num_var)) +
geom_point() + smooth() + xlab("Fitted Values") +
ylab("Studentized Residuals")
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
add a comment |
0
0
0
No reproducible example, but try this:
- don't use
attach(), use thedata=argument tolm()instead (this isn't your actual problem, but is better practice) - use
fitted(fit_num_var), etc. - you might also be interested in the
augmentfunction from thebroompackage
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet,
data=clean_sales)
ggplot(fit_num_var, aes(x=fitted(fit_num_var),
y=residuals(fit_num_var)) +
geom_point() + smooth() + xlab("Fitted Values") +
ylab("Studentized Residuals")
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
No reproducible example, but try this:
- don't use
attach(), use thedata=argument tolm()instead (this isn't your actual problem, but is better practice) - use
fitted(fit_num_var), etc. - you might also be interested in the
augmentfunction from thebroompackage
fit_num_var <- lm(SalePrice ~ ResidentialUnits + CommercialUnits +
YearBuilt + TotalUnits + LandSquareFeet + GrossSquareFeet,
data=clean_sales)
ggplot(fit_num_var, aes(x=fitted(fit_num_var),
y=residuals(fit_num_var)) +
geom_point() + smooth() + xlab("Fitted Values") +
ylab("Studentized Residuals")
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
answered Nov 14 '18 at 15:11
Ben BolkerBen Bolker
135k13228320
135k13228320
add a comment |
add a comment |
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Welcome to Stack Overflow! Could you make your problem reproducible by sharing a sample of your data so others can help (please do not use
str(),head()or screenshot)? You can use thereprexanddatapastapackages to assist you with that. See also Help me Help you & How to make a great R reproducible example?– Tung
Nov 14 '18 at 16:13