fittedvalues: Compute Fitted Values for a Linear Model
In lestat: A Package for Learning Statistics
Description
Usage
Arguments
Details
Value
Author(s)
See Also
Examples
Description
Given a vector of data values and a design matrix, the fitted values for a
linear model is computed.
Usage
1
fittedvalues(data, design)
Arguments
data
A data vector.
design
A design matrix. The number of rows must be equal to the length of the data vector.
Details
The fitted values represent the expected values all but the last variables in the posterior
for the linear model.
Value
A vector of values of length equal to the number of columns in the design matrix.
Author(s)
Petter Mostad <mostad@chalmers.se>
See Also
linearmodel, leastsquares,
linearpredict
Examples
1
2
3
4
5
xdata <- simulate(uniformdistribution(), 14)
ydata <- xdata + 4 + simulate(normal(), 14)*0.1
plot(xdata,ydata)
design <- cbind(1, xdata)
lines(xdata, fittedvalues(ydata, design))
lestat documentation built on May 2, 2019, 2:09 p.m.
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Description Usage Arguments Details Value Author(s) See Also Examples
Description
Given a vector of data values and a design matrix, the fitted values for a linear model is computed.
Usage
1 | fittedvalues(data, design)
|
Arguments
data |
A data vector. |
design |
A design matrix. The number of rows must be equal to the length of the data vector. |
Details
The fitted values represent the expected values all but the last variables in the posterior for the linear model.
Value
A vector of values of length equal to the number of columns in the design matrix.
Author(s)
Petter Mostad <mostad@chalmers.se>
See Also
linearmodel, leastsquares,
linearpredict
Examples
1 2 3 4 5 | xdata <- simulate(uniformdistribution(), 14)
ydata <- xdata + 4 + simulate(normal(), 14)*0.1
plot(xdata,ydata)
design <- cbind(1, xdata)
lines(xdata, fittedvalues(ydata, design))
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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