::Free Statistics and Forecasting Software::



:: Blocked Bootstrap Plot - Central Tendency - Free Statistics Software (Calculator) ::

All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

This free online software (calculator) computes the Blocked Bootstrap Plot for three measures of Central Tendency: mean, median, and midrange. This method can be applied to univariate, stationary time series.
The following charts are generated by this module: sequences of simulated values (mean, median, and midrange), density trace of each eastimation, and notched boxplots of simulated values.
The blocked bootstrap simulation algorithm is used with a fixed (user-defined) window (blockwidth).

For more information about the bootstrap: Davison, A.C. and Hinkley, D.V. (1997), Bootstrap Methods and Their Application,. Cambridge University Press.

Enter (or paste) your data delimited by hard returns.

Send output to:
[reset data]
# simulations 
blockwidth of bootstrap 
Significant digits 
Chart options

Source code of R module
Top | Output | Charts | References

Cite this software as:
Wessa P., (2019), Blocked Bootstrap Plot for Central Tendency (v1.0.7) in Free Statistics Software (v1.2.1), Office for Research Development and Education, URL https://www.wessa.net/rwasp_bootstrapplot.wasp/
The R code is based on :
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988), The New S Language, Wadsworth & Brooks/Cole.
Chambers, J. M., Cleveland, W. S., Kleiner, B. and Tukey, P. A., (1983), Graphical Methods for Data Analysis., Wadsworth & Brooks/Cole.
Murrell, P. (2005), R Graphics, Chapman & Hall/CRC Press.
NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/, 2006-10-03.
Scott, D. W. (1992), Multivariate Density Estimation. Theory, Practice and Visualization, New York: Wiley.
Sheather, S. J. and Jones M. C. (1991), A reliable data-based bandwidth selection method for kernel density estimation., J. Roy. Statist. Soc. B, 683-690.
Silverman, B. W. (1986), Density Estimation, London: Chapman and Hall.
Venables, W. N. and Ripley, B. D. (2002), Modern Applied Statistics with S, New York: Springer.
S original by Angelo Canty R port by Brian Ripley, boot: Bootstrap R (S-Plus) Functions (Canty), 2005
Top | Output | Charts | References

To cite Wessa.net in publications use:
Wessa, P. (2024), Free Statistics Software, Office for Research Development and Education,
version 1.2.1, URL https://www.wessa.net/

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Software Version : 1.2.1
Algorithms & Software : Patrick Wessa, PhD
Server : www.wessa.net

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