MPC_AAM

Multiple single linear models that minimize absolute area.

There are three distinct approaches for phase error correction, they are: a single linear model with a choice of optimization functions, multiple linear models with optimization function choices and a shrinkage-based method. The methodology is based on our new algorithms and various references (Binczyk et al. (2015) <doi:10.1186/1475-925X-14-S2-S5>,Chen et al. (2002) <doi:10.1016/S1090-7807(02)00069-1>, de Brouwer (2009) <doi:10.1016/j.jmr.2009.09.017>, Džakula (2000) <doi:10.1006/jmre.2000.2123>, Ernst (1969) <doi:10.1016/0022-2364(69)90003-1>, Liland et al. (2010) <doi:10.1366/000370210792434350>).

Aixiang Jiang 

NMRphasing

Phase Error Correction and Baseline Correction for One
Dimensional ('1D') 'NMR' Data

Aixiang Jiang

MPC_AAM function

<dl><dt>specdat</dt>
<dd>A complex number vector of observed frequency domain data.</dd>
<dt>withBC</dt>
<dd>A logical parameter that enables/disables baseline correction after baseline correction</dd></dl>

Arguments

Author

MPC_AAM — MPC_AAM

<dl>

<dt>specdat</dt>
<dd>A complex number vector of observed frequency domain data.</dd>


<dt>withBC</dt>
<dd>A logical parameter that enables/disables baseline correction after baseline correction</dd>

</dl>

MPC_AAM: MPC_AAM

Description

Usage

Value

Arguments

Author

Details

References

Examples