use matrix columns in linear fitHow to sort a dataframe by multiple column(s)Drop data frame columns by nameread.table returning character matrix, would like numericDummy Variables for Data Frame Containing only PredictorsHow to write and read matrix from file without column names?Using 'scan' to read into a matrix in RHow can I read a matrix from a txt file in R?How can I make predictor variables into a matrix?Sort a matrix by last columnMultiple regression in R with matrix columns in model
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use matrix columns in linear fit
How to sort a dataframe by multiple column(s)Drop data frame columns by nameread.table returning character matrix, would like numericDummy Variables for Data Frame Containing only PredictorsHow to write and read matrix from file without column names?Using 'scan' to read into a matrix in RHow can I read a matrix from a txt file in R?How can I make predictor variables into a matrix?Sort a matrix by last columnMultiple regression in R with matrix columns in model
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How to use one column of a numeric matrix as target variable and the remaining columns as predictors?
Somehow this doesn't work
# read matrix with 14 columns
d <- read.table("myfile.txt")
# target variable is last column
y <- d[,14]
x <- d[,-14]
my.fit <- y~x
r
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
add a comment |
How to use one column of a numeric matrix as target variable and the remaining columns as predictors?
Somehow this doesn't work
# read matrix with 14 columns
d <- read.table("myfile.txt")
# target variable is last column
y <- d[,14]
x <- d[,-14]
my.fit <- y~x
r
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
2
There are at least a couple of major problems with your approach. Have you ever done a linear regression in R before? You don't give a function for controlling your data. Your independent variable is literally a pile of numbers. You might start by looking up "r linear regression".
– shea
Mar 24 at 4:41
add a comment |
How to use one column of a numeric matrix as target variable and the remaining columns as predictors?
Somehow this doesn't work
# read matrix with 14 columns
d <- read.table("myfile.txt")
# target variable is last column
y <- d[,14]
x <- d[,-14]
my.fit <- y~x
r
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
How to use one column of a numeric matrix as target variable and the remaining columns as predictors?
Somehow this doesn't work
# read matrix with 14 columns
d <- read.table("myfile.txt")
# target variable is last column
y <- d[,14]
x <- d[,-14]
my.fit <- y~x
r
r
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
asked Mar 24 at 4:25
quantum_wellquantum_well
374314
374314
2
There are at least a couple of major problems with your approach. Have you ever done a linear regression in R before? You don't give a function for controlling your data. Your independent variable is literally a pile of numbers. You might start by looking up "r linear regression".
– shea
Mar 24 at 4:41
add a comment |
2
There are at least a couple of major problems with your approach. Have you ever done a linear regression in R before? You don't give a function for controlling your data. Your independent variable is literally a pile of numbers. You might start by looking up "r linear regression".
– shea
Mar 24 at 4:41
2
2
There are at least a couple of major problems with your approach. Have you ever done a linear regression in R before? You don't give a function for controlling your data. Your independent variable is literally a pile of numbers. You might start by looking up "r linear regression".
– shea
Mar 24 at 4:41
There are at least a couple of major problems with your approach. Have you ever done a linear regression in R before? You don't give a function for controlling your data. Your independent variable is literally a pile of numbers. You might start by looking up "r linear regression".
– shea
Mar 24 at 4:41
add a comment |
1 Answer
1
active
oldest
votes
You can just do:
data(mtcars) #get some preinstalled data
model <- lm(mpg ~ ., data = mtcars) #fit the model
summary(model) #get the summary
This does a linear regression of mpg against all other variables. No further processing required.
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can just do:
data(mtcars) #get some preinstalled data
model <- lm(mpg ~ ., data = mtcars) #fit the model
summary(model) #get the summary
This does a linear regression of mpg against all other variables. No further processing required.
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
add a comment |
You can just do:
data(mtcars) #get some preinstalled data
model <- lm(mpg ~ ., data = mtcars) #fit the model
summary(model) #get the summary
This does a linear regression of mpg against all other variables. No further processing required.
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
add a comment |
You can just do:
data(mtcars) #get some preinstalled data
model <- lm(mpg ~ ., data = mtcars) #fit the model
summary(model) #get the summary
This does a linear regression of mpg against all other variables. No further processing required.
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
You can just do:
data(mtcars) #get some preinstalled data
model <- lm(mpg ~ ., data = mtcars) #fit the model
summary(model) #get the summary
This does a linear regression of mpg against all other variables. No further processing required.
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
answered Mar 24 at 9:16
HumpelstielzchenHumpelstielzchen
2,3211422
2,3211422
add a comment |
add a comment |
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2
There are at least a couple of major problems with your approach. Have you ever done a linear regression in R before? You don't give a function for controlling your data. Your independent variable is literally a pile of numbers. You might start by looking up "r linear regression".
– shea
Mar 24 at 4:41