scb {pamfe} | R Documentation |
Calculates simultaneous confidence bands for the mixed model representation of penalized
splines based on the scbM
function from package AdaptFitOS
. In contrast to the
scbM
function, confidence bands for fixed effects panel data models using the
first-difference estimator (see Puetz and Kneib, 2016) are calculated.
scb(object, drv = 0, level = 0.95, pred = 500, div = 1000, pages = 0)
object |
A |
drv |
The derivative order. Defaults to 0, i.e. the estimated function itself is plotted. First and second derivatives are supported. |
level |
Level of confidence, default is 0.95. |
pred |
Number of grid points used for the plot of confidence bands, default is 500. |
div |
Precision for the integral used for calculation of the length of the curve, default is 1000. |
pages |
The number of pages over which to spread the output. If pages=1 then all terms will be plotted on one page in an automatic fashion. If pages=0 (default) all graphics settings are left as they are. |
The resulting confidence bands have (approximate) frequentist coverage probabilities with automatic bias correction (see references).
Makes use of the volume-of-tube formula and the corresponding code from the libtube
library by Catherine Loader (see package locfit
).
crit |
A list of critical values. |
seqx |
A list of grid points for the plot of confidence bands. |
Stdev |
The standard deviations of estimates. |
sigma2 |
The variance of the residuals. |
drv |
The derivative order. |
fitted |
A list of fitted values. |
lcb |
A list of lower bounds of confidence bands. |
ucb |
A list of upper bounds of confidence bands. |
Peter Puetz ppuetz@uni-goettingen.de
Krivobokova, T., Kneib, T., and Claeskens, G. (2010). Simultaneous confidence bands for penalized spline estimators. Journal of the American Statistical Association, 105(490):852-863.
Puetz, P., Kneib, T. (2016). A Penalized Spline Estimator For Fixed Effects Panel Data Models. https://www.uni-goettingen.de/de/Puetz_03_2016/534166.html
Wiesenfarth, M., Krivobokova, T., Klasen, S., Sperlich, S. (2012). Direct Simultaneous Inference in Additive Models and its Application to Model Undernutrition. Journal of the American Statistical Association, 107(500): 1286-1296.
library(pamfe) # data generation: additive model with time constant indivdual fixed effects id <- rep(1:50,each = 10) years <- rep(1:10,50) x1 <- runif(500) x2 <- runif(500) f1 <- sin(2 * pi * (x1 - 0.5)) ^ 2 f2 <- x2 * (1 - x2) f1_s <- f1 / sd(f1) f2_s <- f2 / sd(f2) fe <- rep(sample(1:100,50),each = 10) y <- fe + f1_s + f2_s + rnorm(500,sd = 0.5) data <- as.data.frame(cbind(id,years,y,x1,x2)) # transform data set to panel data set from type "pdata.frame" from package "plm" pdata <- pdata.frame (data, index = c("id", "years"), row.names = TRUE) # run first-difference penalized spline panel data model with generous amount of knots mod <- pam(y ~ sfe(x1,k = 40) + sfe(x2,k = 40),data = pdata) summary(mod) # look at 99%-confidence bands for estimated functions and its derivatives scb_mod <- scb(mod,level = 0.99,pages = 1) scb_der <- scb(mod,level = 0.99,pages = 1,drv = 1)