Description Usage Arguments Details Value Author(s) References See Also Examples
To compute the conditional probability density function from data with measurement error. The measurement errors have to be homoscedastic.
1 2 |
y |
The observed data. It is a vector of length at least 3. |
sig |
The standard deviations σ. If homoscedastic errors, sig is a single value. If heteroscedastic errors, sig is a vector of standard deviations having the same length as y. |
y0 |
The given conditional data point in the conditional density f(x|y=y0). |
error |
Error distribution types: (1) 'normal' for normal errors; (2) 'laplacian' for Laplacian errors; (3) 'snormal' for a special case of small normal errors. |
bw1 |
The bandwidth for the deconvolution density f_X. It can be a single numeric value which has been pre-determined; or computed with the specific bandwidth selector: 'dnrd' to compute the rule-of-thumb plugin bandwidth as suggested by Fan (1991); 'dmise' to compute the plugin bandwidth by minimizing MISE; 'dboot1' to compute the bootstrap bandwidth selector without resampling (Delaigle and Gijbels, 2004a), which minimizing the MISE bootstrap bandwidth selectors; 'boot2' to compute the smoothed bootstrap bandwidth selector with resampling. |
bw2 |
The bandwidth for the kernel density f_Y. It can be a single numeric value which has been pre-determined; or computed with the specific bandwidth selector: 'nrd0','nrd','ucv', 'bcv', and 'SJ' (see the "density" function in R). |
adjust |
adjust the range there the PDF is to be evaluated. By default, adjust=1. |
fft |
To specify the method to compute the PDF. 'fft=FALSE' to compute directly; 'fft=TRUE' to compute the PDF by using the Fast Fourier Transformation. |
n |
number of points where the conditional PDF is to be evaluated. |
from |
the starting point where the conditional PDF is to be evaluated. |
to |
the starting point where the conditional PDF is to be evaluated. |
cut |
used to adjust the starting end ending points where the conditional PDF is to be evaluated. |
na.rm |
is set to FALSE by default: no NA value is allowed. |
grid |
the grid number to search the optimal bandwidth when a bandwidth selector was specified in bw. Default value "grid=100". |
ub |
the upper boundary to search the optimal bandwidth, default value is "ub=2". |
tol |
the parameter to avoid the estimate of f(y|x) too small. The default vaule is 0. It can not exceed 0.05. |
... |
control |
If the number of points to be evaluated is too small (less than 32), a direct computing method is preferred. The current version can support up to 2^21 points where the conditional PDF to be computed.
An object of class “Decon”.
X.F. Wang wangx6@ccf.org
B. Wang bwang@jaguar1.usouthal.edu
Fan, J. (1991). On the optimal rates of convergence for nonparametric deconvolution problems. The Annals of Statistics, 19, 1257-1272.
Wang XF, Ye D (2010). Conditional density estimation with measurement error. Technical Report.
Wang, X.F. and Wang, B. (2011). Deconvolution estimation in measurement error models: The R package decon. Journal of Statistical Software, 39(10), 1-24.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | n <- 1000
x <- c(rnorm(n/2,-2,1),rnorm(n/2,2,1))
sig <- .8
u <- rnorm(n,sd=sig)
w <- x+u
f1 <- DeconCPdf(w,sig, y0=-2.5, error='normal')
f2 <- DeconCPdf(w,sig, y0=0, error='normal')
f3 <- DeconCPdf(w,sig, y0=2.5, error='normal')
par(mfrow=c(2,2))
plot(density(w), main="f_w", xlab="w")
plot(f1, main="f1", xlab="x")
plot(f2, main="f2", xlab="x")
plot(f3, main="f3", xlab="x")
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