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Table 1 Characteristics of preconditioned (deflated) coefficient matrices, and of PCG and DPCG methods for solving ssSNPBLUP applied to the reduced dataset

From: A second-level diagonal preconditioner for single-step SNPBLUP

\(\text{Model}^{\mathrm{a}}\)

\(\text{Method}^{\mathrm{b}}\)

\(k_{O}^{\mathrm{c}}\)

\(k_{S}^{\mathrm{c}}\)

\(k_{O}/k_{S}\)

\(\lambda _{min}^{\mathrm{d}}\)

\(\lambda _{max}^{\mathrm{d}}\)

\(\kappa ^{\mathrm{e}}\)

\(\textit{N}^{\mathrm{f}}\)

MS

PCG

1

1

1

\(1.07\times 10^{-04}\)

\(1.81\times 10^{2}\)

\(1.70\times 10^{6}\)

1499

MS

PCG

1

2

0.5

\(1.07\times 10^{-04}\)

\(9.11\times 10^{1}\)

\(8.55\times 10^{5}\)

1103

MS

PCG

1

3.3

0.3

\(1.07\times 10^{-04}\)

\(5.51\times 10^{1}\)

\(5.17\times 10^{5}\)

862

MS

PCG

1

\(10^{1}\)

\(10^{-1}\)

\(1.07\times 10^{-04}\)

\(1.91\times 10^{1}\)

\(1.79\times 10^{5}\)

560

MS

PCG

1

\(10^{2}\)

\(10^{-2}\)

\(1.07\times 10^{-04}\)

\(1.19\times 10^{1}\)

\(1.12\times 10^{5}\)

417

MS

PCG

1

\(10^{3}\)

\(10^{-3}\)

\(1.06\times 10^{-04}\)

\(1.19\times 10^{1}\)

\(1.12\times 10^{5}\)

608

MS

PCG

1

\(10^{4}\)

\(10^{-4}\)

\(4.86\times 10^{-05}\)

\(1.19\times 10^{1}\)

\(2.45\times 10^{5}\)

1254

MS

PCG

1

\(10^{5}\)

\(10^{-5}\)

\(4.87\times 10^{-06}\)

\(1.19\times 10^{1}\)

\(2.45\times 10^{6}\)

2350

MS

PCG

\(10^{-1}\)

1

\(10^{-1}\)

\(1.07\times 10^{-03}\)

\(1.91\times 10^{2}\)

\(1.79\times 10^{5}\)

557

MS

PCG

\(10^{-2}\)

1

\(10^{-2}\)

\(1.07\times 10^{-02}\)

\(1.19\times 10^{3}\)

\(1.12\times 10^{5}\)

416

MS

PCG

\(10^{-3}\)

1

\(10^{-3}\)

\(1.06\times 10^{-01}\)

\(1.19\times 10^{4}\)

\(1.12\times 10^{5}\)

606

MS

PCG

\(10^{-4}\)

1

\(10^{-4}\)

\(4.86\times 10^{-01}\)

\(1.19\times 10^{5}\)

\(2.45\times 10^{5}\)

1254

MS

PCG

\(10^{-5}\)

1

\(10^{-5}\)

\(4.86\times 10^{-01}\)

\(1.19\times 10^{6}\)

\(2.45\times 10^{6}\)

2367

MS

DPCG (1)

1

1

1

\(1.09\times 10^{-04}\)

6.44

\(5.93\times 10^{4}\)

294

MS

DPCG (1)

1

\(10^{5}\)

\(10^{-5}\)

\(1.09\times 10^{-04}\)

6.44

\(5.92\times 10^{4}\)

293

MS

DPCG (5)

1

1

1

\(1.07\times 10^{-04}\)

6.44

\(6.03\times 10^{4}\)

342

MS

DPCG (5)

1

\(10^{1}\)

\(10^{-1}\)

\(1.07\times 10^{-04}\)

6.44

\(6.03\times 10^{4}\)

331

MS

DPCG (5)

1

\(10^{2}\)

\(10^{-2}\)

\(1.07\times 10^{-04}\)

6.44

\(6.04\times 10^{4}\)

385

MS

DPCG (5)

1

\(10^{3}\)

\(10^{-3}\)

\(1.06\times 10^{-04}\)

6.44

\(6.05\times 10^{4}\)

544

MS

DPCG (5)

1

\(10^{4}\)

\(10^{-4}\)

\(4.96\times 10^{-05}\)

6.44

\(1.30\times 10^{5}\)

961

MS

DPCG (5)

1

\(10^{5}\)

\(10^{-5}\)

\(4.95\times 10^{-06}\)

6.44

\(1.30\times 10^{6}\)

1456

Liu

PCG

1

1

1

\(1.06\times 10^{-04}\)

\(6.98\times 10^{1}\)

\(6.56\times 10^{5}\)

1401

Liu

PCG

1

\(10^{1}\)

\(10^{-1}\)

\(1.06\times 10^{-04}\)

\(1.19\times 10^{1}\)

\(1.12\times 10^{5}\)

561

Liu

PCG

1

\(10^{2}\)

\(10^{-2}\)

\(1.06\times 10^{-04}\)

\(1.19\times 10^{1}\)

\(1.12\times 10^{5}\)

563

Liu

PCG

1

\(10^{3}\)

\(10^{-3}\)

\(5.91\times 10^{-05}\)

\(1.19\times 10^{1}\)

\(2.02\times 10^{5}\)

1154

Liu

DPCG (5)

1

1

1

\(1.07\times 10^{-04}\)

6.44

\(6.05\times 10^{4}\)

419

Liu

DPCG (5)

1

\(10^{1}\)

\(10^{-1}\)

\(1.07\times 10^{-04}\)

6.44

\(6.05\times 10^{4}\)

399

Liu

DPCG (5)

1

\(10^{2}\)

\(10^{-2}\)

\(1.06\times 10^{-04}\)

6.44

\(6.05\times 10^{4}\)

520

Liu

DPCG (5)

1

\(10^{3}\)

\(10^{-3}\)

\(6.02\times 10^{-05}\)

6.44

\(1.07\times 10^{5}\)

1046

  1. \({}^{\mathrm{a}}\)MS = ssSNPBLUP model proposed by Mantysaari and Stranden [7]; Liu = ssSNPBLUP model proposed by Liu et al. [5]
  2. \({}^{\mathrm{b}}\)Number of SNP effects per subdomain is within brackets
  3. \({}^{\mathrm{c}}\)Parameters used for the second-level preconditioner \({\mathbf{D}}\)
  4. \({}^{\mathrm{d}}\)Smallest and largest eigenvalues of the preconditioned (deflated) coefficient matrix
  5. \({}^{\mathrm{e}}\)Condition number of the preconditioned (deflated) coefficient matrix
  6. \({}^{\mathrm{f}}\)Number of iterations. A number of iterations equal to 10,000 means that the method failed to converge within 10,000 iterations