Name

fac_pca1 — Static factor analysis

CALLING SEQUENCE

res=fac_pca1(x,snum,pnum,baing,meth)

PARAMETERS

Input

• x = a matrix of data

• snum = a vector of factors to keep (e.g. [1,…,k]) or the maximum number of factor to test (here k) if the Bai-Ng information criteria is used

• pnum = number of factors to keep for the printing of results

• baing = 'Icp1', 'ICp2', 'ICp3' or 'no' type of Bai-Ng criteria to use

• meth = 'stan' if the user wants to perform the analysis on standardized variables

Output

• res = a results tlist with

  - res('meth') = 'static factor'

  - res('namex') = vector of names of the x variables

  - res('x') = matrix of x data

  - res('fi') = first factor selected by the user (in TS format when working with TS) it's the factor i i.e the i-th most important contributor to total variance

  - res('fj') = second factor selected by the user it's the factor j i.e the j-th most important contributor to total variance and so on

  - res('propor') = proportion of variance explained by each factor

  - res('corr_x_f') = matrix of correlations between variables and factors default is the first five factors)

  - res('loadings') = matrix of loadings (variables are in rows) (default is the first five factors)

  - res('snum') = number of selected factor by the user of Bai-Ng (default is the first factor)

  - res('pnum') = number of selected factor for printing results (default is the first five factors)

  - res('bai_ng')= 'no','ICp1','ICp2', 'ICp3'

  - res('ICpk') = value of information criteria selected for each of the number of factor tested

DESCRIPTION

Performs the estimation of a Static factor analysis with the selection of the number of factors according to one of the information criteria proposed by Bai-Ng. NOTE: can also be used as an approximate dynamic factor analysis (see Stock, J. H. and M. Watson (1998), "Diffusion Indexes", NBER Working Paper, n. 6702)

EXAMPLE

r=fac_pca1([y1 y2 y3],1:2,2,'no','stan')
 
 
With y1, y2 and y3 the students achievements in finance, marketing and policy provided by Tryfos (see reference in the text) on standardize variables (option 'stan'), calculates the 2 first factors, stores all results for these 2 factors. The # of factors being imposed by the user, the Bai-Ng option is set to 'no'. 
 
 
               

AUTHOR

Emmanuel Michaux 2006