Elpaso: PM2.5 speciation data from El Paso, Texas, USA.

In mansukoh/bayesMRM: Bayesian Multivariate Receptor Modeling

Description

The data frame has the following components:

• Y 224 by 15 matrix of 224 observations on 15 PM2.5 species. PM 2.5 was measured every three days during the time period of 1/2/2006 ~ 4/7/2009 from the Chamizal station in the city of El Paso, USA. Out of the 58 original PM 2.5 species, 15 species were selected. After removing any observations with missig values, the final data consists of 224 complete observatins on the following 15 PM2.5 species:

  Al

  Aluminum

  Ca

  Calcium

  Cl2

  Chlorine

  EC

  EC CSN

  Fe

  Iron

  K_p

  Potassium ion

  Mg

  Magnanese

  NV_NO3

  Non-volatile nitrate

  NH4_p

  Ammonium ion

  Na

  Sodium

  OC

  OC CSN unadjusted

  SO4

  Sulfate

  Si

  Silicon

  Ti

  Titanium

  Zn

  Zinc

• muP 4 by 15 matrix of the prior mean of the source composition matrix P for data. Zero values are assigned for some elements of muP to satisfy the identifiability conditions C1-C2 in Park and Oh (2015). The remaining nonzero elements of muP have value 0.5. Note that the number of sources (the number of rows in muP) is presumed to be 4 here.

References

Park, E.S. and Oh, M-S. (2016), Bayesian Quantile Multivariate Receptor Modeling, Chemometrics and intelligent laboratory systems, 159, 174-180.

Examples

data(Elpaso)
Y=Elpaso$Y
muP=Elpaso$muP

mansukoh/bayesMRM documentation built on March 19, 2021, 3:50 p.m.