Best fit line with known offsets.
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Hello all it's my first post on these forums so if I'm breaking any ettiqute feel free to let me know.
So it's been a few years since I took a linear algebra class in college but I remember using Total Least squares to find a best fit line with the errors in both the x and y variables to give you a line with errors that were perpendicular to the created line.
I'd like program something similar to this with the difference being that not all of my data points actually land on said line. Some of them are intentional perpendicular offsets on both sides of the line that have known distances.
I've searched the internet for a similar problem but I've yet to find anything similar. Maybe I don't know the right terms to search for.
Does this sound like a possible problem? Any nudge in right direction would be helpful.
Thanks in advance.
Calvin
linear-algebra least-squares
asked Nov 20 at 7:01
andHobbes
11
add a comment |
up vote
0
down vote
favorite
Hello all it's my first post on these forums so if I'm breaking any ettiqute feel free to let me know.
So it's been a few years since I took a linear algebra class in college but I remember using Total Least squares to find a best fit line with the errors in both the x and y variables to give you a line with errors that were perpendicular to the created line.
I'd like program something similar to this with the difference being that not all of my data points actually land on said line. Some of them are intentional perpendicular offsets on both sides of the line that have known distances.
I've searched the internet for a similar problem but I've yet to find anything similar. Maybe I don't know the right terms to search for.
Does this sound like a possible problem? Any nudge in right direction would be helpful.
Thanks in advance.
Calvin
linear-algebra least-squares
asked Nov 20 at 7:01
andHobbes
11
So did I understand correctly, that you want to do linear regression, but filter out some outliers?
– Matti P.
Nov 20 at 7:08
You could look into algorithms such as RANSAC or least trimmed squares.
– Qidi
Nov 20 at 7:12
No not quite. Let me add some context. I am a land surveyor and I have found monuments along a straight line in the center of a roadway. I have also found monuments at the edge of the road that are 25 foot offsets. I'd like to use both the centerline monuments and the right-of-way monuments to best fit a line.
– andHobbes
Nov 20 at 7:14
1
If you know what offsets they (are supposed to) have, why not just move them by that offset, then do regular linear regression?
– Arthur
Nov 20 at 7:17
I know the amount they need to be moved but not the direction because the offsets are perpendicular to the line I'm attempting to create. My data set is a group of x,y coordinate pairs with an offset component of 0 for on line or -25 for 25 feet left of the line or 25 for 25 feet right of the line.
– andHobbes
Nov 20 at 7:24
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
Hello all it's my first post on these forums so if I'm breaking any ettiqute feel free to let me know.
So it's been a few years since I took a linear algebra class in college but I remember using Total Least squares to find a best fit line with the errors in both the x and y variables to give you a line with errors that were perpendicular to the created line.
I'd like program something similar to this with the difference being that not all of my data points actually land on said line. Some of them are intentional perpendicular offsets on both sides of the line that have known distances.
I've searched the internet for a similar problem but I've yet to find anything similar. Maybe I don't know the right terms to search for.
Does this sound like a possible problem? Any nudge in right direction would be helpful.
Thanks in advance.
Calvin
linear-algebra least-squares
asked Nov 20 at 7:01
andHobbes
11
Hello all it's my first post on these forums so if I'm breaking any ettiqute feel free to let me know.
So it's been a few years since I took a linear algebra class in college but I remember using Total Least squares to find a best fit line with the errors in both the x and y variables to give you a line with errors that were perpendicular to the created line.
I'd like program something similar to this with the difference being that not all of my data points actually land on said line. Some of them are intentional perpendicular offsets on both sides of the line that have known distances.
I've searched the internet for a similar problem but I've yet to find anything similar. Maybe I don't know the right terms to search for.
Does this sound like a possible problem? Any nudge in right direction would be helpful.
Thanks in advance.
Calvin
linear-algebra least-squares
linear-algebra least-squares
asked Nov 20 at 7:01
andHobbes
11
asked Nov 20 at 7:01
andHobbes
11
asked Nov 20 at 7:01
andHobbes
11
asked Nov 20 at 7:01
andHobbes
11
asked Nov 20 at 7:01
andHobbes
11
11
So did I understand correctly, that you want to do linear regression, but filter out some outliers?
– Matti P.
Nov 20 at 7:08
You could look into algorithms such as RANSAC or least trimmed squares.
– Qidi
Nov 20 at 7:12
No not quite. Let me add some context. I am a land surveyor and I have found monuments along a straight line in the center of a roadway. I have also found monuments at the edge of the road that are 25 foot offsets. I'd like to use both the centerline monuments and the right-of-way monuments to best fit a line.
– andHobbes
Nov 20 at 7:14
1
If you know what offsets they (are supposed to) have, why not just move them by that offset, then do regular linear regression?
– Arthur
Nov 20 at 7:17
I know the amount they need to be moved but not the direction because the offsets are perpendicular to the line I'm attempting to create. My data set is a group of x,y coordinate pairs with an offset component of 0 for on line or -25 for 25 feet left of the line or 25 for 25 feet right of the line.
– andHobbes
Nov 20 at 7:24
add a comment |
So did I understand correctly, that you want to do linear regression, but filter out some outliers?
– Matti P.
Nov 20 at 7:08
You could look into algorithms such as RANSAC or least trimmed squares.
– Qidi
Nov 20 at 7:12
No not quite. Let me add some context. I am a land surveyor and I have found monuments along a straight line in the center of a roadway. I have also found monuments at the edge of the road that are 25 foot offsets. I'd like to use both the centerline monuments and the right-of-way monuments to best fit a line.
– andHobbes
Nov 20 at 7:14
1
If you know what offsets they (are supposed to) have, why not just move them by that offset, then do regular linear regression?
– Arthur
Nov 20 at 7:17
I know the amount they need to be moved but not the direction because the offsets are perpendicular to the line I'm attempting to create. My data set is a group of x,y coordinate pairs with an offset component of 0 for on line or -25 for 25 feet left of the line or 25 for 25 feet right of the line.
– andHobbes
Nov 20 at 7:24
So did I understand correctly, that you want to do linear regression, but filter out some outliers?
– Matti P.
Nov 20 at 7:08
So did I understand correctly, that you want to do linear regression, but filter out some outliers?
– Matti P.
Nov 20 at 7:08
You could look into algorithms such as RANSAC or least trimmed squares.
– Qidi
Nov 20 at 7:12
You could look into algorithms such as RANSAC or least trimmed squares.
– Qidi
Nov 20 at 7:12
No not quite. Let me add some context. I am a land surveyor and I have found monuments along a straight line in the center of a roadway. I have also found monuments at the edge of the road that are 25 foot offsets. I'd like to use both the centerline monuments and the right-of-way monuments to best fit a line.
– andHobbes
Nov 20 at 7:14
No not quite. Let me add some context. I am a land surveyor and I have found monuments along a straight line in the center of a roadway. I have also found monuments at the edge of the road that are 25 foot offsets. I'd like to use both the centerline monuments and the right-of-way monuments to best fit a line.
– andHobbes
Nov 20 at 7:14
1
1
If you know what offsets they (are supposed to) have, why not just move them by that offset, then do regular linear regression?
– Arthur
Nov 20 at 7:17
If you know what offsets they (are supposed to) have, why not just move them by that offset, then do regular linear regression?
– Arthur
Nov 20 at 7:17
I know the amount they need to be moved but not the direction because the offsets are perpendicular to the line I'm attempting to create. My data set is a group of x,y coordinate pairs with an offset component of 0 for on line or -25 for 25 feet left of the line or 25 for 25 feet right of the line.
– andHobbes
Nov 20 at 7:24
I know the amount they need to be moved but not the direction because the offsets are perpendicular to the line I'm attempting to create. My data set is a group of x,y coordinate pairs with an offset component of 0 for on line or -25 for 25 feet left of the line or 25 for 25 feet right of the line.
– andHobbes
Nov 20 at 7:24
add a comment |
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So did I understand correctly, that you want to do linear regression, but filter out some outliers?
– Matti P.
Nov 20 at 7:08
You could look into algorithms such as RANSAC or least trimmed squares.
– Qidi
Nov 20 at 7:12
No not quite. Let me add some context. I am a land surveyor and I have found monuments along a straight line in the center of a roadway. I have also found monuments at the edge of the road that are 25 foot offsets. I'd like to use both the centerline monuments and the right-of-way monuments to best fit a line.
– andHobbes
Nov 20 at 7:14
1
If you know what offsets they (are supposed to) have, why not just move them by that offset, then do regular linear regression?
– Arthur
Nov 20 at 7:17
I know the amount they need to be moved but not the direction because the offsets are perpendicular to the line I'm attempting to create. My data set is a group of x,y coordinate pairs with an offset component of 0 for on line or -25 for 25 feet left of the line or 25 for 25 feet right of the line.
– andHobbes
Nov 20 at 7:24