Description Usage Arguments Details Value Note References See Also Examples
imcmtn()
is used to fit a linear regression model based on the Monte Carlo Method using truncated normal distribution.
1 |
formula |
an object of class |
data |
an data frame containing the variables in the model. |
b |
number of resampling (default : 100) |
Similar to imcmuni()
, but uses a truncated normal distribution rather than a uniform distribution.
resampling.coefficients |
B coefficient vectors obtained by resampling. |
coefficients |
Average of B coefficients obtained by resampling, standard error and p-value. |
fitted.values |
The fitted values for the lower and upper interval bound. |
residuals |
The residuals for the lower and upper interval bound. |
In dataset, a pair of the interval variables should always be composed in order from lower to upper bound. In order to apply this function, the data should be composed as follows:
y_L | y_U | x1_L | x1_U | x2_L | x2_U |
y_L1 | y_U1 | x_L11 | x_U11 | x_L12 | x_U12 |
y_L2 | y_U2 | x_L21 | x_U21 | x_L22 | x_U22 |
y_L3 | y_U3 | x_L31 | x_U31 | x_L32 | x_U32 |
y_L4 | y_U4 | x_L41 | x_U41 | x_L42 | x_U42 |
y_L5 | y_U5 | x_L51 | x_U51 | x_L52 | x_U52 |
The upper limit value of the variable should be unconditionally greater than the lower limit value. Otherwise, it will be output as NA
or NAN
, and the value can not be generated.
Ahn, J., Peng, M., Park, C., Jeon, Y.(2012), A Resampling Approach for Interval-Valued Data Regression. Statistical Analysis and Data Mining, 5, 336-348
Lim, S., Kang, K.(2016), On Statistical Analysis of Interval-Valued Data
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