no non-missing arguments to max; returning -Infno

[Programming-Skills]

Hi, I have simulated some IPD, and have run nphsim::combo.wlr and got results. However, when I run:

result.rmst <- nphsim::rmst.Stat(survival = IPD.sim.crossing$time, cnsr = IPD.sim.crossing$event, trt = IPD.sim.crossing$arm, stra = NULL, fparam = 30)

On the IPD given below, I get this error:

no non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -Infno non-missing arguments to max; returning -InfNaNs producedNaNs produced

time,event,arm
0.04,1,0
0.29,1,0
0.3,1,0
0.32,1,0
0.39,1,0
0.51,1,0
0.53,1,0
0.57,1,0
0.59,1,0
0.67,1,0
0.69,1,0
0.71,1,0
0.76,1,0
0.77,1,0
0.99,1,0
0.99,1,0
1,1,0
1.01,1,0
1.06,1,0
1.07,1,0
1.07,1,0
1.09,1,0
1.1,1,0
1.15,1,0
1.19,1,0
1.19,1,0
1.23,1,0
1.48,1,0
1.5,1,0
1.52,1,0
1.6,1,0
1.71,1,0
1.8,1,0
1.82,1,0
1.89,1,0
1.91,1,0
2.02,1,0
2.29,1,0
2.59,1,0
2.61,1,0
2.61,1,0
2.71,1,0
2.78,1,0
2.86,1,0
2.86,1,0
2.87,1,0
2.98,1,0
3.03,1,0
3.05,1,0
3.11,1,0
3.22,1,0
3.33,1,0
3.33,1,0
3.4,1,0
3.45,1,0
3.57,1,0
3.69,1,0
3.78,1,0
3.78,1,0
3.83,1,0
3.84,1,0
4.01,1,0
4.13,1,0
4.14,1,0
4.16,1,0
4.17,1,0
4.23,1,0
4.24,1,0
4.42,1,0
4.43,1,0
4.44,1,0
4.73,1,0
4.75,1,0
4.79,1,0
5.14,1,0
5.18,1,0
5.19,1,0
5.23,1,0
5.27,1,0
5.42,1,0
5.48,1,0
5.57,1,0
5.78,1,0
5.84,1,0
5.87,1,0
5.93,1,0
6.12,1,0
6.35,1,0
6.4,1,0
6.48,1,0
6.49,1,0
6.5,1,0
6.55,1,0
6.66,1,0
6.79,1,0
7.04,1,0
7.37,1,0
7.76,1,0
7.8,1,0
8.14,1,0
8.22,1,0
8.76,1,0
8.83,1,0
8.88,1,0
9,1,0
9.38,1,0
9.46,1,0
9.9,1,0
10.45,1,0
10.68,1,0
10.96,1,0
11.47,1,0
11.55,1,0
11.88,1,0
11.93,1,0
12.06,1,0
12.06,1,0
12.11,1,0
12.31,1,0
12.52,1,0
13.07,1,0
13.11,1,0
13.33,1,0
13.64,1,0
13.65,1,0
14.05,1,0
14.1,1,0
15.13,1,0
15.34,1,0
15.34,1,0
16.6,1,0
16.66,1,0
16.76,1,0
16.94,1,0
17.19,1,0
17.39,1,0
17.49,1,0
17.8,1,0
17.84,1,0
17.89,1,0
18.22,1,0
18.3,1,0
18.49,1,0
18.82,1,0
19.23,1,0
19.48,1,0
20.32,1,0
22.05,1,0
22.61,1,0
22.82,1,0
23.87,1,0
24.73,1,0
24.81,1,0
25.1,0,0
25.13,1,0
25.15,1,0
25.24,0,0
25.3,1,0
25.49,1,0
25.84,0,0
27.93,0,0
28.18,0,0
30.16,0,0
31.75,0,0
33.69,0,0
0.05,1,1
0.09,1,1
0.39,1,1
0.55,1,1
0.67,1,1
0.79,1,1
0.89,1,1
0.9,1,1
1,1,1
1.1,1,1
1.14,1,1
1.27,1,1
1.37,1,1
1.37,1,1
1.46,1,1
1.56,1,1
1.61,1,1
1.67,1,1
1.68,1,1
1.72,1,1
1.78,1,1
1.84,1,1
2.03,1,1
2.04,1,1
2.1,1,1
2.18,1,1
2.25,1,1
2.28,1,1
2.45,1,1
2.49,1,1
2.72,1,1
2.79,1,1
3.04,1,1
3.29,1,1
3.46,1,1
3.48,1,1
3.54,1,1
3.61,1,1
3.62,1,1
3.71,1,1
3.8,1,1
3.95,1,1
4.07,1,1
4.11,1,1
4.16,1,1
4.22,1,1
4.23,1,1
4.26,1,1
4.27,1,1
4.32,1,1
4.35,1,1
4.39,1,1
4.45,1,1
4.47,1,1
4.55,1,1
4.57,1,1
4.58,1,1
4.67,1,1
4.67,1,1
4.89,1,1
5.02,1,1
5.03,1,1
5.03,1,1
5.05,1,1
5.08,1,1
5.16,1,1
5.23,1,1
5.24,1,1
5.29,1,1
5.33,1,1
5.34,1,1
5.4,1,1
5.47,1,1
5.49,1,1
5.51,1,1
5.61,1,1
5.78,1,1
5.89,1,1
6.17,1,1
6.47,1,1
6.82,1,1
7.05,1,1
7.18,1,1
7.18,1,1
7.19,1,1
7.23,1,1
7.31,1,1
7.84,1,1
7.98,1,1
8.09,1,1
8.68,1,1
8.89,1,1
8.95,1,1
8.97,1,1
9.16,1,1
9.28,1,1
9.3,1,1
9.35,1,1
9.47,1,1
9.49,1,1
9.49,1,1
9.61,1,1
9.63,1,1
9.64,1,1
9.74,1,1
9.78,1,1
9.83,1,1
9.88,1,1
10.01,1,1
10.06,1,1
10.16,1,1
10.2,1,1
10.43,1,1
10.51,1,1
10.63,1,1
10.65,1,1
10.67,1,1
10.74,1,1
11.01,1,1
11.23,1,1
11.6,1,1
11.8,1,1
11.84,1,1
11.85,1,1
11.92,1,1
12.01,1,1
12.01,1,1
12.16,1,1
12.23,1,1
12.31,1,1
12.34,1,1
12.36,1,1
12.69,1,1
12.69,1,1
12.86,1,1
13.59,1,1
13.8,1,1
13.84,1,1
13.92,1,1
14.27,1,1
14.41,1,1
14.47,1,1
14.58,1,1
14.68,1,1
14.95,1,1
15.14,1,1
15.15,1,1
15.2,1,1
15.35,1,1
15.5,1,1
15.51,1,1
15.56,1,1
15.9,1,1
15.91,1,1
15.96,1,1
16.61,1,1
17.6,1,1
17.68,1,1
20.13,1,1
20.23,1,1
20.35,1,1
24.73,0,1
26.44,1,1
26.89,0,1
31.95,1,1

Not quite sure, what's wrong with this data.