I am doing a microRNA-mRNA paired expression analysis and because of collinearities between the miRNAs covariates and large number of microRNAs (in comparison to the sample size), ordinary linear regression model is not applicable. Therefor I thought about partial least square (PLS) regression methods. Has anybody performed such an analysis on miR-mRNA data? Would be grateful if anybody recommend some R/Python scrip?
It case is to be handled with the problem of collinearity not partial least sq. As I understand.
Dear Ali
In SPSS, the calculations of the measures above can be easily developed . See,
Landau, S. and Everitt, B. S.(2004). A Handbook of Statistical analyses
Howitt, D. and Cramer, D.(2008). Introduction to SPSS.
Regards,
Zuhair
You can apply method of curve fitting based on elimination-minimization principle or method of least squares in inverse order.
For this, go through the following papers:
1. Atwar Rahman & Dhritikesh Chakrabarty (2009) : “Linear Curve : A Simpler Method of Obtaining Least squares Estimates of Parameters ”, Int. J. Agricult. Stat. Sci., (ISSN : 0973 - 1903), 5(2), 415 – 424.
2. Dhritikesh Chakrabarty (2011) : “Finite Difference Calculus: Method of Determining Least Squares Estimates ”, AryaBhatta J. Math. & Info. , 3 (2), (ISSN : 0975 – 7139), 363 – 373. Also available in www.abjni.com .
3. Atwar Rahman & Dhritikesh Chakrabarty (2011) : “General Linear Curve : A Simpler Method of Obtaining Least squares Estimates of Parameters ”, Int. J. Agricult. Stat. Sci., (ISSN : 0973 - 1903), 7(2), 429 – 440.
4. Dhritikesh Chakrabarty (2014) : “Curve Fitting: Step-Wise Least Squares Method ”, AryaBhatta J. Math. & Info. , 6(1), (ISSN : 0975 – 7139), 15 – 24.
5. Atwar Rahman & Dhritikesh Chakrabarty (2015) : “Elimination of Parameters and Principle of Least Squares: Fitting of Linear Curve to Average Minimum Temperature Data in the Context of Assam ”, International Journal of Engineering Sciences & Research Technology, 4(2), (ISSN : 2277 - 9655), 255 – 259.
6. Atwar Rahman & Dhritikesh Chakrabarty (2015) : “ Elimination of Parameters and Principle of Least Squares: Fitting of Linear Curve to Average Maximum Temperature Data in the Context of Assam ”, AryaBhatta J. Math. & Info. (ISSN (Print): 0975 – 7139, ISSN (Online): 2394 – 9309), 7(1), 23 – 28, Also available in www.abjni.com .
7. Atwar Rahman & Dhritikesh Chakrabarty (2015) : “ Basian-Markovian Principle in Fitting of Linear Curve ”, The International Journal Of Engineering And Science, {ISSN (e): 2319 – 1813 ISSN (p): 2319 – 1805} www.theijes.com), 4(6), 31 – 43.
8. Atwar Rahman & Dhritikesh Chakrabarty (2015) : “Basian-Markovian Principle in Fitting of Quadratic Curve ”, International Research Journal of Natural and Applied Sciences (ISSN: 2349 - 4077), www.aarf.asia , 2(6), 186 – 210.
9. Atwar Rahman & Dhritikesh Chakrabarty (2015) : “ Method of Least Squares in Reverse Order: Fitting of Linear Curve to Average Minimum Temperature Data at Guwahati and Tezpur”, AryaBhatta J. Math. & Info. {ISSN (Print): 0975 – 7139, ISSN (Online): 2394 – 9309}, 7(2), 305 – 312, Also available in www.abjni.com .
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